ОБНАРУЖЕНИЕ БОЛЕЗНЕЙ РАСТЕНИЙ С ПОМОЩЬЮ МНОГОСТАДИЙНОГО, МНОГОМАСШТАБНОГО ГЛУБОКОГО ОБУЧЕНИЯ

Группа изобретений относится к области распознавания изображений и может быть использована для распознавания болезней растений. Техническим результатом является повышение точности распознавания. Способ распознавания содержит следующие этапы: получение процессором нового изображения от пользовательского устройства; применение процессором первой цифровой модели, обученной для отнесения множества первых областей внутри нового изображения к множеству классификаций, выбранных из первой группы болезней растений, имеющих симптомы с размером в пределах первого диапазона, здорового состояния или сборного класса для комбинации болезней растений, имеющих симптомы других размеров; применение процессором второй цифровой модели, обученной для отнесения одной или более второй области, которые отнесены первой цифровой моделью к сборному классу, к одной или более классификациям, которые выбраны из болезни растений, имеющей симптомы в пределах второго диапазона, здорового состояния или сборного класса для ...

Wine label recognition method, wine information management method and apparatus, device, and storage medium

Provided are a wine label recognition method, a wine information management method and apparatus, a computer device, and a computer-readable storage medium. The method comprises: acquiring a wine image, and performing OCR recognition on the wine image according to a pre-configured OCR recognition method so as to acquire text comprised in the wine image (S21); performing deep learning recognition on the wine image according to a pre-configured deep learning recognition method so as to acquire an image feature comprised in the wine image (S22); and acquiring, from a pre-configured wine label database by means of screening and according to the text and the image feature, a target wine label matching the text and the image feature, and using the target wine label as a wine label corresponding to the wine image (S23). Deep learning is used to overcome the shortcomings of OCR text recognition in wine label text recognition within a complex environment where a wine is located, and OCR text recognition ...

Tool for counting and sizing plants in a field

The application relates to agricultural technology and artificial intelligence, to counting and sizing plants in a field. One aspect relates to a method for analysing plants in an area of interest that generally includes providing at least one aerial image of the area of interest, performing object detection, segmentation and instantiation using an object-mask-predicting region convolutional neural network, Mask R-CNN, wherein the Mask R-CNN is trained to detect a selected vegetable. The numbers and sizes of objects detected is determined by dividing the area of interest into multiple cells, calculating the average object size per cell and displaying results in the form of a map of the area of interest with colour or scale for each cell corresponding to the average size of object in the cell.

HEATING COOKER, CONTROL DEVICE, AND CONTROL METHOD

A heating cooker includes a heating chamber, an imaging device, a heating device, and control device (). Control device () includes captured image acquisition unit (), heating information acquisition unit (), heating controller (), and state detector (). Captured image acquisition unit () acquires an image captured by the imaging device. Heating information acquisition unit () acquires heating information by referring to the image of a heating target acquired. Heating controller () controls the heating device according to the heating information. State detector () detects presence or absence of the heating target in the heating chamber or removal of the heating target from the heating chamber by referring to the image captured. Heating information acquisition unit () acquires the heating information when state detector () detects absence of the heating target in the heating chamber or removal of the heating target from the heating chamber. 1. A heating cooker comprising:a heating chamber having an opening;a door covering the opening of the heating chamber;an imaging device operable to capture an image inside the heating chamber;a heating device operable to heat a heating target placed inside the heating chamber; anda control device,wherein a captured image acquisition unit operable to acquire the image captured by the imaging device,', 'a heating information acquisition unit operable to acquire heating information by referring to the image acquired by the captured image acquisition unit, and', 'a heating controller operable to control the heating device according to the heating information, and', 'a state detector operable to detect presence or absence of the heating target in the heating chamber or removal of the heating target from the heating chamber by referring to the image captured by the imaging device, and, 'the control device includesthe heating information acquisition unit is operable to acquire the heating information when the state detector detects ...

SYSTEMS AND METHODS FOR MANAGING MEAT CUT QUALITY

In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

Methods and systems for identifying internal conditions in juvenile fish through non-invasive means

Methods and systems are disclosed for improvements in aquaculture that allow for increasing the number and harvesting efficiency of fish in an aquaculture setting by identifying and predicting internal conditions of the juvenile fish based on external characteristics that are imaged through non-invasive means.

FOOD INSPECTION SOLUTION

CULTIVATION SYSTEM HAVING CULTIVATION BOX AND CONTROLLING METHOD THEREOF

Recognition apparatus and method

SYSTEM FOR MONITORING GLUTEN CONSUMPTION AND PREDICTING ASSOCIATION OF INDISPOSITION TO GLUTEN CONSUMPTION

A system for monitoring gluten consumption, especially in celiac people, which allows the feeding of food consumption data and updating, in real time, of the estimated amount of gluten consumed daily. Still, the present invention refers to a system for prediction that associates the possibility of an indisposition being associated or not with an undue consumption of gluten.

Retail checkout terminal fresh produce identification system

Disclosed are systems and methods including starting with a first number of images, generating a second number of images by digital operations on the first number of images, extracting features from the second number of images, and generating a classification model by training a neural network on the second number of images wherein the classification model provides a percentage likelihood of an image's categorisation, embedding the classification model in a processor and receiving an image for categorisation, wherein the processor is in communication with a POS system, the processor running the classification model to provide output to the POS system of a percentage likelihood of the image's categorisation.

Comparing planogram compliance to checkout data

The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.

REDUCING SCALE ESTIMATE ERRORS IN SHELF IMAGES

Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.

FEEDBUNK VOLUME ESTIMATION VIA IMAGE SEGMENTATION

System and method for sorting and/or packing items

Apparatus and method for determining food characteristics

An apparatus for determining a characteristic of food on a dish, comprises at least two imaging devices comprising an optical camera and a thermal camera. Each camera is configured to capture an image of the dish. The apparatus also comprises a processor configured to receive an image from the cameras, determine the characteristic of the food on the dish in dependence on the image, and output an indicator indicative of the characteristic being representative of a suitability of the food on the dish for consumption. The two cameras may be configured to capture images of the dish from different angles. At least one of the imaging devices may be configured to capture a first image of the dish at a first time, and a second image of the dish at a second time different to the first time, and the processor may be configured to receive the second image from the imaging device and determine a second characteristic of the food on the dish in dependence on the second image or on a comparison between ...

Systems and methods for predicting crop size and yield

A computer system obtains, in electronic format, a training dataset. The training dataset comprises a plurality of training images from a plurality of agricultural plots. Each training image is from a respective agricultural plot in the plurality of agricultural plots and comprises at least one identified fruit. The computer system determines, for each respective fruit in each respective training image in the plurality of training images, a corresponding contour. The computer system trains an untrained or partially trained computational model using at least the corresponding contour for each respective fruit in each respective training image in the plurality of training images, thereby obtaining a first trained computational model that is configured to identify fruit in agricultural plot images.

SYSTEM AND METHOD FOR SORTING AND/OR PACKING ITEMS

An item packing system configured to sort and/or pack items into item containers, the system comprising a robotic arm. At least one end effector for holding and manipulating an item to be sorted and/or packed, wherein at least one end effector comprises a pressure sensing assembly. A controller configured to receive sensor signals from the pressure sensing assembly to obtain an indication of a magnitude of contact pressure for contact between the end effector and the item held by the end effector. A direction of contact pressure for contact between the end effector and the item held by the end effector, wherein the controller is configured to determine whether the end effector is correctly holding the item based on the indication of the magnitude of the contact pressure and the indication of the direction of contact pressure.

Video processing

System and method for measuring dish size and providing nutrition information using image recognition and augmented reality based on artificial intelligence

Disclosed are a system and a method for measuring dish size and providing nutritional information using image recognition and augmented reality based on artificial intelligence. The system includes: at least one imaging device acquiring at least one image including at least one dish or at least one food contained in each dish; a service providing apparatus for detecting the at least one dish and the at least one food from the at least one image when the at least one image is received, confirming the name of each detected food on the basis of a learning model, predicting the size of each detected dish, predicting the volume of each detected food using the predicted size of the dish, and generating nutritional information using the predicted volume of each food and pre-stored food information; and a user terminal for visualizing and displaying the nutritional information when the nutritional information is received.

Systems and methods for managing meat cut quality

In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

METHOD FOR TRAINING A MACHINE ABLE TO DETERMINE CHARACTERISTICS OF PLANT ELEMENTS

INDUSTRIALIZED SYSTEM FOR RICE GRAIN RECOGNITION AND METHOD THEREOF

METHOD FOR PROCESSING PLANTS IN A FIELD

METHOD FOR OPERATING ON AN ENVIRONMENT

A method of operating on an environment (100) comprising the steps of capturing one or more image streams of the environment (10); generating one or more environment-representative signals (Setl) as a function of the captured image streams; acquiring one or more environment datasets (Set2); sending the environment-representative signals (Setl) and the environment datasets (Set2) to the intermediate processing unit (1300); generating an environment signal (Se) as a function of the representative signals (Setl) and the environment dataset (Set2); sending the environment signal (Se) to the central processing unit (1400); comparing the environment signal (Se) with reference signals (Sr) associated with the selected environment (10); generating, using data processing algorithms, residing in the central processing unit (1400) as a function of the comparison between the environment signal (Se) and the reference signals (Sr): an action signal (Sa) representative of an operation to be performed ...

СПОСОБ И УСТРОЙСТВО ИДЕНТИФИКАЦИИ РОЗНИЧНЫХ ТОВАРОВ

Изобретение относится к способам распознавания розничных товаров, расположенных на полках стеллажей супермаркета. Устройство идентификации товара содержит камеру, соединенную с инерциальным измерительным блоком и детектором, вычислительный блок, соединенный с инерциальным измерительным блоком и детектором, базу данных, блок сравнения, соединенный с вычислительным блоком и базой данных. Для идентификации товара производят съемку изображения стеллажа с товарами посредством камеры. Определяют угол между оптической осью камеры при съемке и направлением гравитации. Обнаруживают изображение товара с полки, попавшего на отснятое изображение. Определяют положение центра каждого ограничивающего прямоугольника на изображении, отснятом камерой. Вычисляют угол между горизонтальной плоскостью и лучом, соединяющим центр объектива камеры и центр ограничивающего прямоугольника. Извлекают из базы данных набор изображений известных товаров, из которого выбирают изображение, которое имеет наибольшую степень ...

Estimation of crop type and/or sowing date

Method, apparatus, and computer program product are provided for estimating crop type and/or sowing date. A historical crop growth time series and a plurality of simulated crop growth time series are determined, and the historical time series is matched against each simulated time series to determine an estimated crop type and/or sowing date. For example, one simulated time series may be determined for each crop type/sowing date combination within a set of one or more crop types and one or more sowing dates based on historical crop data. Each time series represents crop growth in an area of interest and comprises element(s) including crop-specific parameter(s), such as leaf area index (LAI). The historical time series may be determined based on remote sensor data. Each simulated time series may be determined using a crop growth simulation model and based on historical crop data, geospatial data, and weather data.

Method and apparatus for sorting

An apparatus for sorting is described and includes acquiring a multiplicity of synchronized image signals of a product stream which is to be sorted; generating a multiplicity of fused sensor signals; forming an image model previously acquired from the objects to be sorted; identifying objects in the product stream, and generating object presence and defect signals; determining a spatial orientation of the objects in the product stream; detecting the defects and removing the defects from the product stream.

METHOD FOR GENERATING A PLURALITY OF ANNOTATED IMAGES

A crop scanning system, parts thereof, and associated methods

A crop scanning system for determining a parameter associated with a plurality of harvestable items of a crop, the harvestable items such as tubers or potatoes being beneath a ground surface, the crop scanning system including: a scanning head (11, figs.4-6) assembly including at least one scanning device (111, figs.4-6) configured to perform a scanning operation in relation to the harvestable items, the scanning device being configured to emit a ground penetrating radar signal or pulse and to generate scan data including a representation of the harvestable items; an imaging system configured to capture an image of a part of the crop which is above the ground surface and to generate image data including a representation of one or more stems associated with the harvestable items; and an analysis system configured to use the scan data and the image data to determine the parameter associated with the harvestable items, wherein the at least one parameter includes a predicted size of the harvestable ...

Refrigerator

According to an embodiment of the present disclosure, a refrigerator may include a storage compartment, a door, one or more cameras provided in the door, a global DB configured to store a plurality of default food identification items and a plurality of default product names respectively corresponding to the plurality of default food identification items, and a local DB configured to store edited product names and a food identification item corresponding to the edited product names, and a processor configured to photograph an internal image of the storage compartment, obtain one or more food identification items from the photographed internal image, and if the obtained one or more food identification items are stored in the local DB, recognize one or more product names of the obtained one or more food identification items as product names of the food identification items stored in the local DB.

Image-based kitchen tracking system with anticipatory preparation management

The subject matter of this specification can be implemented in, among other things, methods, systems, computer-readable storage medium. A method can include receiving, by a processing device, image data including one or more image frames indicative of a current state of a meal preparation area. The processing device determines a first quantity of a first ingredient disposed within a first container based on the image data. The processing device determines a meal preparation procedure associated with the first ingredient based on the first quantity. The processing device causes a notification indicative of the meal preparation procedure to be displayed on a graphical user interface (GUI).

Prioritizing shelf-oriented tasks

A system for automatically addressing detected conditions within the retail store is provided. The system may include at least one processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; retrieve reference data specifying a desired state of the retail store; use the reference data to detect an indicator of a first service-improvement condition; use the reference data to detect an indicator of a second service-improvement; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and assign the first product-related task to the first employee and assign the second product-related task to the second employee.

METHOD FOR TREATING FOOD IN AN APPLIANCE, FOOD TREATMENT SYSTEM AND SOFTWARE APPLICATION

A method for treating food in an appliance (14) by at least one treatment device of the appliance (14) comprises the steps of a. providing a food recognition system with at least one camera image of a food item to be treated by the appliance (14)(S1), b. picture data about the food item by extracting a number of at least one characteristic features of the food item from the at least one camera image (S2), c. assigning a food identification to the food item based on at least one of the number of characteristic features (S4, S6), d. executing a food treatment process or program allocated to the assigned food identification (S8). According to the invention, the camera image is provided during step a. (S1) by an external camera device (12, 14), wherein the camera image provision is executed—by data retrieval by the food recognition system, and/or—by data transfer by the mobile camera device (12, 20), and/or—on the operator's initiation. Further disclosed is a food treatment system comprising ...

Diabetic treatment management system

Providing a treatment adjustment plan for a user based on blood glucose data may include obtaining a user profile comprising health information for a user; obtaining, from a camera, image data capturing a food product in front of the user; and identifying the food product based on the image data. Providing the treatment adjustment plan may also include detecting user consumption of the food product; obtaining blood glucose characteristics associated with the food product; determining an estimated blood glucose response based on the blood glucose characteristics and the user profile; and determining a treatment adjustment based on the estimated blood glucose response.

Locating picking points of anomalies

Method and system for sensor maintenance

The method for dirty camera detection including: detecting a first predetermined state change event; sampling a set of cavity measurements; optionally determining a set of features of the set of cavity measurements; determining a class label based on the cavity measurements; optionally verifying the classification; and facilitating use of the appliance based on the classification.

SYSTEM AND METHOD FOR SPACE SEARCH REDUCTION IN IDENTIFYING ITEMS FROM IMAGES VIA ITEM HEIGHT

A device detects a triggering event that corresponds to a placement of a first item on a platform. In response, the device captures an image of the first item and generates a first encoded vector for the image. The first encoded vector describes one or more attributes of the first item. The device determines a height of the first item. The device identifies one or more items in an encoded vector library that are associated with average heights within a threshold range from the determined height of the first item. The device compares the first encoded vector with a second encoded vector associated with a second item from among the one or more items. The device determines that the first encoded vector corresponds to the second encoded vector. In response, the device determines that the first item corresponds to the second item.

COOKED LEVEL DETERMINATION

In an embodiment, a cooking method (100) is described. The method comprises receiving (102) image data corresponding to a view of a food item during a cooking process implemented by a cooking apparatus. The method further comprises identifying (104) a region of interest in the view. The region of interest comprises an indication of liquid leached out from the food item as a result of the cooking process. The method further comprises determining (106) a cooked level of the food item based on a distribution of the liquid on a surface in the view and a parameter value indicative of the cooked level of the food item. The parameter value is derived from a part of the image data that corresponds to the region of interest.

REFRIGERATOR, SERVER AND METHOD OF CONTROLLING THEREOF

A server includes a memory storing instructions and a processor configured to execute the instructions to obtain an inside-fridge image captured in a refrigerator by comparing a pre-stored image to the obtained inside-fridge image, identify whether a change area in which a change occurred in the obtained inside-fridge image is present in the obtained inside-fridge image, based on the change area being not present in the obtained inside-fridge image, obtain first food storage information, using a first result of recognizing the pre-stored image, based on the change area being present in the obtained inside-fridge image, obtain second food storage information, using the obtained first food storage information and a second result of recognizing an object included in the obtained inside-fridge image, and transmit, to the refrigerator, the obtained inside-fridge image and either one or both of the obtained first food storage information and the obtained second food storage information.

Method of using, apparatus, product, and system for a no touch point-of-sale self-checkout

A method, computer program product, and system to perform a sale transaction are provided. The method includes identifying each item of a plurality of items, based on at least one image of the plurality of items, determining a cost for each item, optionally identifying a person based on an image of the person, adding each of the items and each of the costs to a sale transaction, and charging the person for the sale transaction.

AUTOMATED IDENTIFICATION OF FISH FILETS

One disclosed method involves encoding an acquired image of a fish filet into a first feature vector consumable by at least one predictive model, processing, with the at least one predictive model, the first feature vector to identify a type of fish from which the fish filet was cut, and causing at least one device to output an indication of the type of fish identified by the at least one predictive model. Another disclosed method involves associating first images of fish filets with metadata indicative of one or more types of fish from which the fish filets were cut, using the first images and the metadata to train at least one predictive model to categorize second images of fish filets into the one or more types of fish, and providing the at least one predictive model to at least one device so as to nable the at least one device to output an indication of the one or more types of fish based acquired images of fish filets.

Agricultural crop identification using satellite and crop rotation

In an approach for identifying a crop using satellite observation data and crop rotation data, a processor receives an aerial image of one or more agricultural fields in a pre-determined geographical region from an optical satellite. A processor selects a plurality of points from the aerial image. A processor clips the aerial image into one or more smaller images to generate one or more observed signatures. A processor determines there is a change in a spatial distribution of one or more crops. A processor generates an actual signature from the one or more observed signatures. A processor cross-correlates the actual signature against a plurality of historical reference signatures to determine a degree of similarity. A processor ranks one or more results of the cross-correlation. A processor identifies the one or more crops. A processor calculates a first estimate of an amount of the one or more crops.

VIDEO PROCESSING

A method of assisting a user in preparation of food. The method comprises capturing a video of the user performing one or more steps in the preparation; generating, from the captured video, a machine representation of the performed one or more steps; comparing the generated machine representation to a corpus of one or more pre-existing machine representations, the one or more pre-existing machine representations corresponding to one or more pre-existing videos; based on the comparison, identifying at least one pre-existing machine representation in the corpus which has a similarity relationship with the generated machine representation; and facilitating playback to the user of at least one pre-existing video corresponding to the identified at least one pre-existing machine representation.

PROCESSING APPARATUS, AND PROCESSING METHOD

This invention provides a processing apparatus (10) including a container identification score computation unit (11) that computes an identification score of a container for a product, based on an image to be processed containing the product, a product identification score computation unit (12) that computes an identification score of the product, based on the image to be processed, and a first identification unit (13) that decides identification information of the product, based on the computed identification score of the container and the computed identification score of the product.

Locating picking points of anomalies

A method for removing an anomaly 104A, 104B in a collection of material comprises receiving, by a processor, an image 108 of the collection of material having a plurality of objects 106, identifying the anomaly 104A, 104B from the plurality of objects 106, generating a bounding box 110A, 110B for the anomaly 104A, 104B, generating one or more picking points on the anomaly 104A, 104B, the one or more picking points being configured on at least one balance points of the anomaly 104A, 104B and removing the anomaly 104A, 104B from the collection of material based on the one or more picking points preferably via robotic means. The method may further comprise comparing the area of the bounding box 110A, 110B to a threshold area. If the area of the bounding box 110A, 110B is less than a threshold area and the one or more picking points are generated at the center of the bounding box 110A, 110B. If the area of the bounding box 110A, 110B exceeds a threshold area one or more segmentations of the ...

SYSTEM AND METHOD FOR ITEM IDENTIFICATION USING CONTAINER-BASED CLASSIFICATION

A device detects a triggering event that corresponds to a placement of an item on a platform. In response, the device captures an image of the item and generates a first encoded vector for the image. The first encoded vector describes one or more attributes of the item. The device determines that the item is associated with a first container category based on the one or more attributes of the item. The device identifies one or more items that have been identified as having placed inside a container associated with the first container category. The device displays a list of item options that comprises the one or more items on a graphical user interface (GUI). The device receives a selection of a first item from along the list of item options and identifies the first item as being inside the container.

METHOD FOR ESTIMATING OBJECT PARAMETERS AND ELECTRONIC DEVICE

HOME APPLIANCE HAVING INTERIOR SPACE FOR ACCOMMODATING TRAY AT VARIOUS HEIGHTS AND METHOD OF OBTAINING IMAGE BY HOME APPLIANCE

A home appliance includes: a camera arranged in the interior space; and at least one processor, wherein the at least one processor is configured to: obtain, through the camera, a first image including a tray that is inserted into the interior space; identify, by using the first image, a height at which the tray is inserted in the interior space; determine, according to the height at which the tray is inserted, a setting value related to capturing of an image of the interior space; and obtain, based on the determined setting value, a second image including contents placed on the tray.

Crop harvesting robot

Embodiments relate to a crop harvesting apparatus configured to garner or harvest crops from plants via vacuum suction and sort the garnered crops via a quick-switching gate system. A vacuum source generates the vacuum suction for the apparatus so that crops are garnered (or plucked) from the plant via suction through an end-effector, which are then transferred to a crop sorter by way of tubing that has a smooth inner surface. The crop sorter utilizes a gate system that exploits vacuum suction from the vacuum source and gravity to quickly and effectively sort the garnered crops into a hopper and a rejection bin.

System and method for sorting and/or packing items

System and Method for Sorting and/or Packing Items

An end effector 222 for a robotic arm 214 for manipulating vine fruit comprises a pair of opposing scoops coupled via a connecting portion 490, each opposing scoop comprising a plurality of digits 480 and each digit 480 comprises a pressure sensing means 485 arranged to detect at least one of (i) the magnitude and (ii) the direction of pressure on each of the digits 480 caused by the vine fruit. Each digit 480 may comprise a curved fingertip 487 comprising an extrusion configured to support vine fruit. The end effector 222 may comprise a controller (160 figure 1) to control operation of at least one of the scoop and each digit 480 based on the detected magnitude and/or direction of pressure. The controller (160 figure 1) may determine whether an end effector 222 is correctly holding vine fruit based on an indication of whether the vine fruit is moving relative to the digits 480 and may control the end effector 222 to manipulate at least one of the digits 480 in response to a determination ...

Automated point of sale systems and methods

An automated point of sale system uses one or more cameras to capture images of food products selected by a user for purchase at a food establishment. The point of sale system then compares the images captured to previously captured reference images of such food products being offered at the establishment to find a match for each product, determines the price of each food product the user has selected based on the comparison and match, identifies an account of the user based on a biometric identification of the user and/or reading information from a machine readable token of the user, and automatically causes the account of the user to be charged or debited for the food products identified, thus reducing the check-out time and increasing efficiency of food establishment point of sale systems.

Cooking device, system and method for controlling the cooking device

A method for controlling a cooking device includes the following steps: recording an image of food; implementing a recognition of the recorded image of the food to determine the likelihood that the food corresponds to known foods. If a probability value exceeds a default threshold value, a cooking program associated with the known food is selected and specified to the cooking device. The probability value for the recorded image and the associated food is increased in response to a user subsequently starting the selected cooking program, and reduced in response to the user discarding the selected cooking program. A cooking device includes a primary control unit for controlling the cooking functions; a network interface with a second control unit, and a camera for recording images of the cooking space. The second control unit processes recorded images independently of the primary control unit and transmits them over the network interface.

Recognition apparatus and method

PORTABLE FIELD IMAGING OF PLANT STOMATA

Examples of the disclosure describe systems and methods for identifying, quantifying, and/or characterizing plant stomata. In an example method, a first set of two or more images of a plant leaf representing two or more focal distances is captured via an optical sensor. A reference focal distance is determined based on the first set of images. A second set of two or more images of the plant leaf is captured via the optical sensor, including at least one image captured at a focal distance less than the reference focal distance, and at least one image captured at a focal distance greater than the reference focal distance. A composite image is generated based on the second set of images. The composite image is provided to a trainable feature detector in order to determine a number, density, and/or distribution of stomata in the composite image. 1. A method for plant leaf phenotyping , comprising:capturing, via an optical sensor, a first set of two or more images of a plant leaf representing two or more focal distances;determining a reference focal distance based on the first set of images;capturing, via the optical sensor, a second set of two or more images of the plant leaf, wherein at least one image of the second set of images is captured at a focal distance less than the reference focal distance, and wherein at least one image of the second set of images is captured at a focal distance greater than the reference focal distance;generating a composite image based on the second set of images; andproviding the composite image to a trainable feature detector in order to determine a number, density, and/or distribution of stomata in the composite image.2. The method of claim 1 , wherein the plant is a corn plant.3. The method of or claim 1 , wherein the first set of images and the second set of images are images of an abaxial surface of the plant leaf.4. The method of any one of - claim 1 , further comprising capturing identification data associated with the plant leaf.5 ...

FOOD DISPOSAL TIMING MANAGEMENT DEVICE, FOOD DISPOSAL TIMING MANAGEMENT SYSTEM, AND FOOD DISPOSAL TIMING MANAGEMENT METHOD

Provided is a food disposal time management device capable of managing a disposal time of a plurality of cooked foods being displayed in a display cabinet individually and easily. A fried food disposal time management device 4 for managing a disposal time of fried food X displayed in a hot showcase 1, comprising: an image acquisition unit 41 that acquires an image including images of a plurality of pieces of fried food X being displayed; an individual surface image management unit 42 that manages a surface image included in the image in association with identification information; a time measurement unit 43 that measures a time during which the surface image associated with the identification information is being included in the image; and a determination unit 45 that determines, for each of the plurality of pieces of fried food X, whether the measured time thereof has reached a reference time.

Normalizing counts of plant-parts-of-interest

Implementations are described herein for normalizing counts of plant-parts-of-interest detected in digital imagery to account for differences in spatial dimensions of plants, particularly plant heights. In various implementations, one or more digital images depicting a top of a first plant may be processed. The one or more digital images may have been acquired by a vision sensor carried over top of the first plant by a ground-based vehicle. Based on the processing: a distance of the vision sensor to the first plant may be estimated, and a count of visible plant-parts-of-interest that were captured within a field of view of the vision sensor may be determined. Based on the estimated distance, the count of visible plant-parts-of-interest may be normalized with another count of visible plant-parts-of-interest determined from one or more digital images capturing a second plant.

AN APPARATUS AND METHOD FOR PERFORMING IMAGE-BASED FOOD QUANTITY ESTIMATION

COOKING APPARATUS, CONTROL METHOD THEREOF, HEATING CONTROL METHOD, AND SERVER

The present application provides a cooking apparatus, a control method thereof, a heating control method, and a server. The cooking apparatus comprises heating devices and multiple heating regions, and any one of the heating regions is provided with a heating device, a memory, and a processor. The memory stores a computer program, and the processor is used to implement, when executing the computer program: image information acquisition of food in the cooking apparatus; identifying the image information, and acquiring a food type and a cooking progress of food corresponding to any one of the heating regions; and controlling, according to the food type and the cooking progress of the food, operation of the heating device corresponding to the heating region. The cooking apparatus controls the heating of food by cooking region on the basis of the food type and the cooking progress of the food, thereby achieving uniform food heating, providing a consistent overall cooking temperature, preventing ...

Refrigerator system

A refrigerator system capable of reducing decrease in the accuracy of detecting change in a storage state and reducing a communication load for transmitting images of the inside of a storeroom, which are taken at a plurality of viewpoints to the outside of a refrigerator is provided. To achieve this, the refrigerator system includes: a camera configured to take the images of the inside of the storeroom; a camera moving device configured to move the camera at least in the vertical direction; a communication device configured to transmit the images taken by the camera to the outside of a main body; and a change detecting device configured to detect change in a food-item storage state of each shelf based on the images taken by the camera. The camera takes images of each shelf at a first viewpoint and a second viewpoint. The change detecting device detects change in the food-item storage state of the shelf based on the image taken at the first viewpoint. The communication device transmits, ...

AUTOMATED PLANT TRIMMER

DETECTION OF NUTRIENT DEFICIENCY IN PLANTS

AGRICULTURAL DECISION SUPPORT SYSTEM

Learned model generating method, learned model generating device, product identifying method, product identifying device, product identifying system, and measuring device

A measuring system 1 includes a server 200 identifying a kind of a product from a product image in which the product is included and a measuring device 100 identifying the kind of the product from the target image in which the product is included. The server 200 includes an acquisition unit that acquires a product image and product information relating to a kind of a product, a dividing unit that acquires a plurality of divided imaged by dividing the product image into a plurality of areas, and a generation unit that generates an identifying model by performing machine learning on the basis of a plurality of divided images extracted by an extraction unit that extracts a plurality of divided images satisfying a predetermined condition relating to a shown amount of the product from among the plurality of divided images.

Machine for selectively harvesting plants

A harvester travels along a route within a field and selectively harvests edible crowns ready for harvesting. As the harvester travels along the route, a position of the harvester and/or the edible crowns may be determined using an encoder, imaging device(s), and/or navigational system(s). For example, image(s) captured by the imaging device(s) may be used to determine a location of the edible crowns and/or global positioning satellite (GPS) coordinates may indicate a location of the harvester within the field. These locations may be used for instructing harvesting components to harvest the edible crowns. For example, the harvester may include robotic arms having end effectors that harvest the edible crowns. Knowing the location of the edible crowns and/or the harvester therefore allows for the accurate placement of the end effectors for harvesting the edible crowns.

GENERATION OF TRAINING DATA FOR THE IDENTIFICATION OF A DISH

MACHINE FOR SELECTIVELY HARVESTING PLANTS

A harvester travels along a route within a field and selectively harvests edible crowns ready for harvesting. As the harvester travels along the route, a position of the harvester and/or the edible crowns may be determined using an encoder, imaging device(s), and/or navigational system(s). For example, image(s) captured by the imaging device(s) may be used to determine a location of the edible crowns and/or global positioning satellite (GPS) coordinates may indicate a location of the harvester within the field. These locations may be used for instructing harvesting components to harvest the edible crowns. For example, the harvester may include robotic arms having end effectors that harvest the edible crowns. Knowing the location of the edible crowns and/or the harvester therefore allows for the accurate placement of the end effectors for harvesting the edible crowns.

ARTICLE READING DEVICE

An article reading device according to an embodiment includes a display device and an image capturing device that generates an image of an article. A processor extracts, from the image, first feature data for recognizing the article and second feature data for determining whether to recognize the article based on the first feature data. The processor determines whether to recognize the article. If it is determined to recognize the article, the processor recognizes the article based on the extracted first feature data, and controls the display device to display a recognition result. If it is determined to not recognize the article, extract a barcode from the image, the processor identifies the article based on the extracted barcode, and control the display device to display an identification result. The processor performs a transaction settlement with respect to the recognition result, if any, and the identification result, if any.

SYSTEMS AND METHODS FOR REMOTELY PURCHASING PERISHABLE PRODUCTS

In some embodiments, a system for remotely purchasing perishable products includes a plurality of image capture devices configured to capture images of perishable products, a product image database, a product attribute database, and a control circuit configured to execute computer program modules. An image processing module receives and processes images from the image capture devices to form a composite image. A product identification module identifies and segments the products in the composite image. A product selection module causes an application executed on a remote electronic device operated by a customer to display the composite image and receives from the application a selection of a product to purchase, at least one product attribute, and a quantity of individual product units to purchase. The product selection module identifies the individual product units having the selected product attribute(s) and outputs signaling to cause retrieval of the individual product units.

METHOD FOR AUTOMATIC PHENOTYPE MEASUREMENT AND SELECTION

AUGMENTED REALITY FEEDBACK OF INVENTORY FOR AN APPLIANCE

A food storage system is disclosed. The system comprises an appliance having a cabinet defining an interior, the interior comprising at least one of a shelf, compartment, or drawer configured to store at least one food item, a vision system comprising at least one imager configured to record image data related to the at least one food item stored within the interior, and a controller in communication with the vision system. The controller can be operable to generate an augmented reality representation of the interior. 1. An inventory management system for an appliance , the inventory management system comprising:a holder disposed in an interior of the appliance and configured to store a food item;an imaging device configured to capture an image of the interior;a display in communication with the imaging device configured to present image data corresponding to the image; and determine an identity of the food item;', 'determine a target location for the food item based on the identity of the food item and an environmental condition of the interior; and', 'communicate an instruction to present the image data with an indication of the target location at the display., 'a controller in communication with the imager and the display, the controller configured to2. The inventory management system according to claim 1 , wherein the image data includes an augmented reality representation including a photographic representation of the interior with a digital representation of the food item overlaying a digital representation of a position of the food item in the interior.3. The inventory management system according to claim 2 , wherein the controller is further configured to generate the augmented reality representation based on the identity of the food item.4. The inventory management system according to claim 2 , wherein the indication is a color indicator and the photographic representation of the interior includes the color indicator.5. The inventory management system ...

METHOD AND SYSTEM FOR SENSOR MAINTENANCE

The method for dirty camera detection including: detecting a first predetermined state change event; sampling a set of cavity measurements; optionally determining a set of features of the set of cavity measurements; determining a class label based on the cavity measurements; optionally verifying the classification; and facilitating use of the appliance based on the classification.

SYSTEMS AND METHODS FOR ASSESSMENT OF FOOD ITEM DRYNESS

Described herein are systems and methods for determining dryness of produce using image data. A method can include receiving, by a computing system and from an imaging device, image data of a batch of produce, performing, by the computing system, object detection to identify each produce in a frame of the image data, extracting, by the computing system, temperature values in pixels of the identified produce in the frame, and determining, by the computing system, distribution characteristics of the extracted temperature values. The method can also include predicting, by the computing system, a dryness metric for the batch of produce based on applying a trained model to the determined distribution characteristics. The model can be trained using temperature distributions of other produce, the temperature distributions being annotated based on previous mappings of skewness of the temperature distributions to dryness.

TARGET DETECTION DEVICE, MACHINE LEARNING IMPLEMENTATION DEVICE, TARGET DETECTION PROGRAM, AND MACHINE LEARNING IMPLEMENTATION PROGRAM

A target detection device includes: a first image acquiring unit configured to acquire a first image depicting a subject, which is generated by irradiating the subject with light belonging to a first wavelength group; a second image acquiring unit configured to acquire a second image depicting the subject, which is generated by irradiating the subject with light belonging to a second wavelength group other than the first wavelength group and having a different wavelength from the light with which the subject has been irradiated to generate the first image; and a target detecting unit configured to detect a target included in the subject using the first image and the second image.

METHOD FOR OPERATING A MACHINE FOR HARVESTING AND/OR SEPARATING ROOT CROPS, ASSOCIATED MACHINE AND ASSOCIATED COMPUTER PROGRAM PRODUCT

DYNAMICALLY ADJUSTING TREATMENT BUFFERS FOR PLANT TREATMENTS

As a farming machine travels through a field of plants, the farming machine accesses an image of a field including a plant and receives sensor signals from one or more sensors coupled to the farming machine. The farming machine applies the image and sensor signals to a computer model to determine a spatial relationship between a treatment mechanism of the farming machine and the plant. Determining the spatial relationship produces an uncertainty measurement for an expected position of the treatment mechanism respective to an expected position of the plant. The farming machine adjusts a treatment buffer based on the uncertainty measurement. The farming machine treats the plant in the field by applying the plant treatment to the plant based on the treatment buffer.

AGGREGATE TRAIT ESTIMATION FOR AGRICULTURAL PLOTS

Implementations are described herein for estimating aggregate trait values for agricultural plots. In various implementations, a plurality of images depicting crops in an agricultural plot may be processed using a feature extraction portion of aggregate trait estimation model to generate a corresponding plurality of embeddings. The plurality of embeddings may be combined to obtain a unified representation of the crops in the agricultural plot. Using a prediction portion of the aggregate trait estimation model, the unified representation of the crops may be processed to estimate, as a direct output of the aggregate trait estimation model, an aggregate trait value of the crops in the agricultural plot. Data indicative of the estimated aggregate trait value of the crops in the agricultural plot may be output at a computing device.

Pistachio sorting device

A pistachio sorting device capable of accurately detecting BGY fluorescence emitted from a fluorescent material adhered to a shell of an in-shell pistachio to perform pass/fail determination and sort out defective products at high speed is provided. The pistachio sorting device comprises a lighting device 11 for irradiating in-shell pistachios which are objects to be sorted in an inspection region with ultraviolet light having a maximum peak wavelength within a range of 345 nm to 390 nm, an optical filter 12 for selectively transmitting light within a wavelength range of 500 nm to 600 nm, a sensor 13 for detecting a two-dimensional intensity distribution of the fluorescence transmitted through the optical filter 12 to generate two-dimensional image data indicating a two-dimensional intensity distribution of fluorescence in the inspection region, and a determining device for determining a pass/fail of for each object to be sorted 10 based on the two-dimensional image data.

Harvester for selectively and robotically harvesting crops

A harvester that determines whether edible crowns are ready to be harvested and selectively harvests the edible crowns that are ready for harvesting. The harvester may include sensors, such as an imaging system, for detecting the edible crowns of individual broccoli plants. Image data from the imaging system may be provided as an input to a machine-learning model to determine a maturity (or immaturity) of the edible crowns. If the edible crowns are ready for harvesting, mechanical pickers harvest the edible crowns. For example, the harvester may include robotic arms having end effectors that cut the edible crowns from a remainder of the broccoli plant. The harvester may be configured to continuously harvest the edible crowns as the harvester moves about a field. In some instances, the harvester may include any number of robotic arms for harvesting the edible crowns across multiple rows of broccoli plants.

Image-Based Kitchen Tracking System with Dynamic Labeling Management

The subject matter of this specification can be implemented in, among other things, methods, systems, computer-readable storage medium. A method can include receiving, by a processing device, image data having one or more image frames indicative of a state of a meal preparation area. The method may further include, determining, based on the image data, a first feature characterization of a first meal preparation item associated with the state of the meal preparation area. The method may further include determining that the first feature characterization does not meet object classification criteria for a set of object classifications. The method may further include causing a notification indicating the first meal preparation item and one of an object classification or a classification status corresponding to the first meal preparation item on a graphical user interface (GUI).

PREDICTING SOIL ORGANIC CARBON CONTENT

METHOD AND SYSTEM FOR SCREENING SPECTRAL INDEXES OF RICE RESISTANT TO BACTERIAL BLIGHT

A method and system for screening spectral indexes of rice resistant to bacterial. The method includes: processing spectral data of a test sample by a threshold segmentation algorithm to obtain average spectral information of each spectral image and a proportion of lesions corresponding to each spectral image; training a deep learning algorithm model based on a self-attention mechanism by using the average spectral information of each spectral image and the proportion of the corresponding lesions to construct a regression model for evaluating an area of the lesions; determining an optimal band combination and a weight value corresponding to each band in the optimal band combination based on the regression model for evaluating the area of the lesions, and then determining the spectral indexes; and identifying differences between rice of different genotypes at different times of infection by using the spectral indexes, and screening rice varieties resistant to bacterial blight.

Tracking objects with changing appearances

Implementations are described herein for tracking objects with changing appearances across temporally-disparate images. In various implementations, a first probability distribution over a plurality of classes may be determined for a first biological object depicted in a first image captured at a first point in time. The classes may represent stages of growth of biological objects. Additional probability distribution(s) over the plurality of classes may be determined for candidate biological object(s) depicted in a second image captured at a second point in time subsequent to the first point in time. The candidate biological object(s) may potentially match the first biological object depicted in the first image. Based on a time interval between the first and second points in time, the first probability distribution may be compared to the probability distribution(s) of the candidate biological object(s) depicted in the second image to match one of the candidate biological object(s) depicted ...

PRODUCE QUALITY ASSESSMENT AND PRICING METRIC SYSTEM

Systems and methods described herein can non-destructively determine current produce quality. An evaluation system can, at a first time, receive image data of produce and identify a type of the produce using machine learning techniques. The produce can be sent to an end-consumer retail environment. A quality assessment system can, at a second time, receive, from a user device in the retail environment, a request for a current quality of a particular produce that includes scanned data of that produce. The quality assessment system can identify that produce, retrieve, from a data store, machine learning trained models for identifying quality features of that produce, determine, based on applying the models to the scanned data, a current quality of that produce, and transmit, to the user device, the current quality. The produce's price can also be dynamically adjusted based on the current quality of that produce.

SMART SYSTEM AND METHOD FOR PROVIDING INFORMATION ABOUT GREEN VEGETABLE JUICE

Proposed is a smart method of providing information about green vegetable juice, the method including: obtaining juice-extraction information which includes information about juice-extraction time of the green vegetable juice, information about weight of the green vegetable juice, and information about ingredients for the green vegetable juice; receiving intake information about the green vegetable juice from a user; calculating change in the weight and freshness of stored green vegetable juice based on the juice-extraction information and the intake information; and generating and displaying a smart button with status information about the stored green vegetable juice based on the calculated change in the weight and freshness of the green vegetable juice. By this method, it is possible to intuitively know the weight and the freshness of the stored green vegetable juice.

Pistachio Sorting Device

A pistachio sorting device capable of accurately detecting BGY fluorescence emitted from a fluorescent material adhered to a shell of an in-shell pistachio to perform pass/fail determination and sort out defective products at high speed is provided. The pistachio sorting device comprises a lighting device 11 for irradiating in-shell pistachios which are objects to be sorted in an inspection region with ultraviolet light having a maximum peak wavelength within a range of 345 nm to 390 nm, an optical filter 12 for selectively transmitting light within a wavelength range of 500 nm to 600 nm, a sensor 13 for detecting a two-dimensional intensity distribution of the fluorescence transmitted through the optical filter 12 to generate two-dimensional image data indicating a two-dimensional intensity distribution of fluorescence in the inspection region, and a determining device for determining a pass/fail of for each object to be sorted 10 based on the two-dimensional image data.

Method for controlling cook based on artificial intelligent and intelligent device

A method for controlling cooking based on artificial intelligence and an artificial intelligence device are disclosed. In the method for controlling cooking based on artificial intelligence, it is possible to continuously monitor how food ingredients are progressing by generating reference information including image information of completed dishes using food ingredient image information acquired through a monitoring unit provided in a kitchen appliance (for example, oven) and determining the cooked state of the food ingredients based on the reference information. An artificial intelligence device according to the present disclosure may be linked with an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, devices related to 5G services, and the like.

HEAT TREATMENT MONITORING SYSTEM

A heat treatment monitoring system comprises a sensor unit having at least one sensor to determine current sensor data of food being heated; a processing unit to determine current feature data from the current sensor data; and a monitoring unit adapted to determine a current heating process state in a current heating process of the monitored food by comparing the current feature data with reference feature data of a reference heating process.

IDENTIFYING STORED PRODUCTS IN DOMESTIC STORAGE DEVICES

OBJECT RECOGNATION SYSTEM AND METHOD OF REGISTERING A NEW OBJECT

MONITORING PRODUCT SHORTAGES OVER TIME

Methods, systems, and computer-readable storage media for processing images captured in a retail store and automatically identifying a product shortage are provided. In one implementation, a system may access information describing a desired placement of products on at least one store shelf. The system may analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold. The system may analyze a second image captured at a second time later than the first time to determine that a second quantity of products is below the quantity threshold. The system may avoid initiating an unscheduled action to cause restocking until a third time later than the second time. Based on a determination that a third quantity of products at the third time are below the quantity threshold, the system may provide information indicative of a product shortage.

FOOD PRODUCT POSITION AND RECOGNITION COOKING AND/OR HOLDING DEVICE SYSTEM

A cooking and/or heat retention appliance, in particular a commercial cooking appliance, comprising a housing in which a cooking or interior space is arranged having a cooking or interior space opening; an insert rack arranged in the cooking or interior space and includes a plurality of pairs of insert rails arranged one above the other for receiving one food product carrier each on insertion levels of different heights; and an optical recognition system arranged above the cooking or interior space opening and includes an image recording device, wherein the image recording device is connected to a separate evaluation device via a data line which, by an evaluation algorithm, determines the positioning of one or more food product carriers in the cooking or interior space and/or the positioning of at least one food product arranged on the food product carrier from the cooking or interior space image data recorded by the image recording device and transmitted to the evaluation device.

SYSTEMS, METHODS, AND APPARATUS FOR IMAGE-RESPONSIVE AUTOMATED ASSISTANTS

Techniques described herein enable a user to interact with an automated assistant and obtain relevant output from the automated assistant without requiring arduous typed input to be provided by the user and/or without requiring the user to provide spoken input that could cause privacy concerns (e.g., if other individuals are nearby). The assistant application can operate in multiple different image conversation modes in which the assistant application is responsive to various objects in a field of view of the camera. The image conversation modes can be suggested to the user when a particular object is detected in the field of view of the camera. When the user selects an image conversation mode, the assistant application can thereafter provide output, for presentation, that is based on the selected image conversation mode and that is based on object(s) captured by image(s) of the camera.

SYSTEMS AND METHODS FOR REAL-TIME OCCUPANCY DETECTION AND TEMPERATURE MONITORING OF COOKING UTENSILS FOR FOOD PROCESSING ASSISTANCE

In one embodiment, a method for monitoring a kitchen environment by a smart hood includes accessing sensor data indicating parameters of a cooking utensil detected by the smart hood apparatus from sensors of the smart hood apparatus, wherein the sensors comprise one or more of a camera, a thermal sensor, an audio sensor, or an air particle sensor, determining occupancy information associated with the cooking utensil based on the sensor data by algorithms, wherein the occupancy information indicates whether the cooking utensil is placed within an allowable deviation from a target location on a cooktop, determining a thermal state of an accessory associated with the cooking utensil based on the sensor data by the algorithms, and sending instructions for presenting the occupancy information associated with the cooking utensil and the thermal state of the accessory.

COOKING APPARATUS AND CONTROLLING METHOD THEREOF

A cooking apparatus is provided. The cooking apparatus includes a camera configured to obtain a cooking image by capturing a food product, a sensor configured to detect information associated with cooking while the food product is being captured, a display, a memory, and a processor configured to store information on a cooking history in the memory by matching the cooking image obtained by the camera and information associated with the cooking which is detected through the sensor, control the display to provide a user interface (UI) capable of setting a degree of cooking based on the stored cooking history, obtain control information of the cooking apparatus based on information associated with the cooking which is matched to the cooking image selected on the provided UI, and control the cooking apparatus to perform cooking based on the obtained control information of the cooking apparatus.

Plant group identification

A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.

OBJECT DETECTION FOR A DOMESTIC APPLIANCE

Ein Verfahren zum Erkennen eines Objekts im Bereich eines Hausgeräts umfasst Schritte des Abtastens eines Kamerabilds, welches das Objekt darstellt, vom Hausgerät aus; des Erfassens einer Seitenkanal-Information; wobei die Seitenkanal-Information einen Umstand betrifft, unter dem das Kamerabild abgetastet wird; und des Erkennens des Objekts mittels eines ML-Systems auf der Basis des Kamerabilds und der Seitenkanal-Information.

AUTOMATED UNSUPERVISED LOCALIZATION OF CONTEXT SENSITIVE EVENTS IN CROPS AND COMPUTING EXTENT THEREOF

Existing techniques in precision farming comprise supervised event detection and need labeled training data which is tedious considering the large number of crops, differences therein and even larger number of diseases and pests. The present disclosure provides an unsupervised method and uses images of any size captured in an uncontrolled environment. The methods and systems disclosed find application in automatically localizing and classifying events, including health state and growth stage and also estimating an extent of manifestation of the event. Information of spatial continuity in pixels and boundaries in a given image is used to update the feature representation and label assignment to every pixel using a fully convolutional network. Back propagation of the pixel labels modified according to the output of a graph based method helps the neural network to converge and provide a time efficient solution.

Smart Doors for Retail Storage Containers

Methods, systems, and computer-readable media are provided for providing information on electronic visual displays in retail stores. In one implementation, a door for a retail storage container may include at least a first part that is configured to face customers when the door is closed and a second part configured to face the internal side of the retail storage container when the door is closed. Further, the second part may include at least an electronic visual display configured to display information, and at least part of the electronic visual display may be configured to be visible to the customers at least when the door is open at a selected angle.

Image processing apparatus and method

An information processing apparatus comprises a category recognition section, a characteristic recognition section and a specifying section. The category recognition section recognizes the category of a commodity using input imaged images. The characteristic recognition section recognizes the characteristics of a specific attachment attached to the commodity using the input imaged images. The specifying section specifies the specific information of the commodity according to the category of the commodity that is recognized by the category recognition section and the characteristics of the specific attachment recognized by the characteristic recognition section.

Soybean cultivar

The present invention is in the field of soybean variety EC1661152, EC1661470, EC1661291, AND/OR EC1661249 breeding and development. The present invention particularly relates to the soybean variety EC1661152, EC1661470, EC1661291, AND/OR EC1661249 and its seed, cells, germplasm, plant parts, and progeny, and methods of using EC1661152, EC1661470, EC1661291, AND/OR EC1661249 in a breeding program.

Dynamic cost function calculation for agricultural users

The dynamic estimation of the cost functions involved in agriculture to determine which crops will result in the best return on investment given local conditions. A user interface allows a user to define a predetermined geographic area for analysis. A processor retrieves historical data encompassing the predetermined geographic area from a database and crop yield factor information from aerial images of the area and uses that information to calculate a minimized cost function for any particular crop to be grown in the area. A user may also select sub-areas for further analysis, for intercropping, and to assess the cost functions for multiple crops.

Method and system for crop type identification using satellite observation and weather data

A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.

Commodity recognition apparatus and commodity recognition method

The commodity recognition apparatus displays a frame for surrounding a commodity in an image captured by an image capturing module. Then the commodity recognition apparatus recognizes a candidate of the commodity imaged in the frame according to the feature amount of the image in the area surrounded by the frame, and outputs information of a highest ranked candidate commodity. If a change instruction for the candidate is received, the commodity recognition apparatus outputs information of the commodity other than the highest ranked candidate selected from the candidates.

Heat-cooking device, heat-cooking device control method, and heat-cooking system

A heat-cooking device includes shape information reading and analyzing unit (204), information storage unit (205), and controller (203). In a case where shape information read by shape information reading and analyzing unit (204) has been registered in information storage unit (205), the heat-cooking device performs heating control based on heating control information registered in information storage unit (205) with being associated with the shape information. In a case where the shape information read by shape information reading and analyzing unit (204) has not been registered in information storage unit (205), a shape of a label attached to an object to be heated or a character printed on the label is read from an image taken by imaging unit (202), and the heat-cooking device performs heating control based information thus read.

Systems and methods for managing meat cut quality

In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

Non-spectroscopic imaging of plants

Monitoring stress symptoms in plants is crucial to maximize crop productivity. Nondestructive imaging of physiological changes in plants has been intensively used as invaluable tools in the agricultural industry. However, this approach requires a bulky and expensive optical instrument for capturing full spectral information and often has intrinsic limitations for quantitative analyses. Disclosed herein are a method and system for spectrometerless hyperspectral imaging that can map out detailed spatial distribution of chlorophyll content, which is a key trait for physiological condition of plants. The combination of a handheld-type imaging system and a hyperspectral reconstruction algorithm offers the simplicity for instrumentation and operation avoiding the use of an imaging spectrograph. This imaging platform can be integrated into a compact, inexpensive, and portable imager for plant biologists and ecophysiologists.

Updating online store inventory based on physical store inventory

A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period.

Augmented reality-enhanced food preparation system and related methods

A food preparation system is configured to enhance the efficiency of food preparation operations in a commercial kitchen by displaying instructions on a surface in the kitchen work area. The food preparation system includes a plurality of cameras aimed at a kitchen workspace for preparing the plurality of food items and a processor operable to compute an instruction for a kitchen worker to perform a food preparation step based on one or more types of information selected from order information, recipe information, kitchen equipment information, data from the cameras, and food item inventory information. A projector in communication with the processor visually projects the instruction onto a location in the kitchen workspace for the kitchen worker to observe. Related methods for projecting food preparation instructions are described.

Object recognition apparatus and method for managing data used for object recognition

An apparatus for managing data used for object recognition includes an image capturing unit configured to capture an image of an object, a storage unit storing image data of products registered for sale, an operation panel configured to receive a user selection, and a processor configured to determine the products registered for sale that are similar to the object, based on the captured image and the image data, display the similar products on the operation panel as user selectable items, determine one or more of the similar products designated by the user selection, and invalidate the designated similar products so that efficiency of object recognition by the apparatus can be improved.

Systems and methods for computer assisted operation

An augmented reality method includes selecting an image of an object to be installed; converting the image into a 3D model; capturing a view of an environment and selecting a place to insert the 3D model; overlaying the 3D model with the view of the environment in a mashed-up and aligned manner wherein the 3D model view is displayed contemporaneously and contiguously to form an augmented reality view; and enabling user interaction with the displayed 3D model view to update the 3D model of the environment in the 3D modeling system.

Forage harvester

A forage harvester is disclosed. The forage harvester has at least one work assembly for processing harvested material of a crop, which includes grain components. In operation, the harvested material is transported in a harvested material flow along a harvested material transport path through the forage harvester. The forage harvester further includes a corn cracker as a work assembly and a control assembly that includes an optical measuring system. The optical measuring system has a camera for recording image data of the harvested material, with the camera being positioned after the corn cracker. The control assembly, using an image recognition routine, determines image regions assigned to a comminuted grain component in the image data, determines geometric properties of the assigned comminuted grain components based on the image regions, and determines an indicator of a processing quality of the comminuted grain components from the geometric properties.

Commodity recognition apparatus and commodity recognition method

A candidate output element configured to output recognition target commodities as candidates of a recognized commodity in a descending order of the similarity degrees calculated by the similarity degree calculation element, a distance measurement element configured to measure the distance from the image capturing section to a commodity photographed by the image capturing section, and a changing element configured to change the number of candidates of a recognized commodity output by the candidate output element according to the distance measured by the distance measurement element.

Interactive touch screen device for wine

Interactive display and rendering device, system and method for wine bottles. are disclosed. An interactive wine management and display device and method using a scanning instrument capable of scanning information regarding a bottle of wine; an imaging instrument capable of collecting an image of at least a portion of a bottle of wine; a connection to a wine database containing information regarding wines; a connection to a database having images of wine bottles. The device is able to render the images as well as information on the wine to a display for user interaction.

Method and system for determination of quantity of food consumed by users

The present disclosure discloses a method and a system for determining quantity of food consumed by users. The method comprising receiving one or more inputs from a first set of sensors and a second set of sensors associated with the determination unit, where the first set of sensors and the second set of sensors monitor one or more users and food served to the one or more users respectively, identifying each type of food from the food served, identifying each of the one or more users and actions performed by each of the one or more users to consume the food and determining quantity of each type of food consumed by each of the one or more users based on the identified actions performed by each of the one or more users.

Carbonization time point management service providing system for cooking fish-meat stuff

Provided is a carbonization time point management service providing system when food stuff such as fish or meat (or fish-meat stuff) cooked, the system receives, from a cooking management service providing server, fish-meat detecting information including a cooking time from a cooking start point in time of fish-meat stuff to a carbonization time point at which the fish-meat stuff starts to be carbonized, generates a cooking completion acquisition signal in accordance with an end timing of the cooking time, and transmits a cooking completion indication signal to cooking management dedicated application content, so that the cooking completion indication signal is externally displayed, thereby enabling real-time confirmation of a cooking process of fish-meat stuff which is placed on a heating device even in the case of performing the other work at the remote place during cooking of the fish-meat stuff, to improve convenience when cooking the fish-meat stuff.

Image processing apparatus

Provided is an image processing apparatus which is connected to and accessible to a database storing a plurality of pieces of previously prepared reference data, and which stores at least one piece of individual data having an image captured by the user in association with the information regarding the food/beverage contained in the captured image. The image processing apparatus compares information of the food/beverage in the captured image with the reference data stored in the database and the individual data, and acquires the food/beverage information included in the reference data together with the reference image similar to the captured image, the food/beverage information associated with the captured image in the individual data, or the food/beverage information in the reference data or the individual data including the food/beverage information relating to the captured image.

FOOD STORAGE SYSTEM, METHOD AND COMPUTER READABLE MEDIUM

Systems and methods for sharing data about the contents of storage bags or containers with external devices are described herein. In several embodiments, a food storage system can operate to track/record data about the contents in multiple storage bags and to allow for the identification of the contents in the storage bags based on a unique identifier associated with the storage bags. In some embodiments, the food storage system can provide reminders, recommendations, or other prompts regarding the contents in the storage bags. 1. A food storage system , comprising:at least one processor; and receive, from a user device, data related to a storage bag that uniquely identifies the storage bag;', 'receive, from the user device, data related to contents of the storage bag;', 'associate the data related to the storage bag with the data related to the contents of the storage bag;', 'generate a notification based on the data related to the contents of the storage bag; and', 'send the notification to the user device., 'at least one non-transitory processor-readable medium storing processor-executable instructions that, when executed by the at least one processor, cause the at least one processor to2. The food storage system of claim 1 , wherein the at least one processor is further configured to generate the notification to be indicative of:a cooking recommendation based on the data related to the contents of the storage bag; and/ora consumption recommendation based on the data related to the contents of the storage bag.3. The food storage system of or claim 1 , wherein the data related to the storage bag is indicative of a machine readable identifier printed on or affixed to the storage bag claim 1 , wherein the machine-readable identifier is a unique identifier.4. The food storage system of any of to claim 1 , wherein the at least one processor is configured to:receive, from the user device, a query request indicative of data uniquely identifying the storage bag having ...

Aggregating product shortage information

A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the retail stores and determine durations associated with the occurrences; identify a common factor contributing to the duration of part of the occurrences of the product shortages; determine an action, associated with the at least one common factor, for potentially reducing product shortage durations of future shortages of the product type in the retail stores; and provide information associated with the identified action to an entity.

Monitoring product shortages over time

A system for processing images captured in a retail store and automatically identifying a product shortage is provided. The system may comprise at least one processor configured to: access information describing a placement of products; receive image data from an image sensor; analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold; analyze a second image captured at a second time to determine that a second quantity is below the quantity threshold; based on the determination that the first quantity exceeds the quantity threshold, avoid initiating an unscheduled action to cause restocking the store shelf with products until a third time; analyze a third image captured at the third time to determine that a third quantity is below the quantity threshold; and based on the determination, provide information indicative of a product shortage at the store shelf.

Vine Growing Management Method and Apparatus With Autonomous Vehicles

In some embodiments, a method for managing growing vine in a vineyard includes operating one or more unmanned aerial vehicles (UAV) to fly over a plurality of sections of a vineyard. The UAVs are fitted with a plurality of cameras equipped to generate images in a plurality of spectrums. The plurality of sections of the vineyard grow vines of a plurality of varietals. The method further includes taking a plurality of aerial images of the sections of the vineyard in the plurality of spectrums, using the plurality of cameras, while the UAVs are flying over the plurality of sections of the vineyard, and executing an analyzer on a computing system to machine analyze the plurality of aerial images for anomalies associated with growing the vines of the plurality of varietals. The machine analysis takes into consideration topological information of the vineyard, as well as current planting information of the vineyard.

Image-based inventory estimation

In an approach to estimating product inventory count, one or more computer processors receive one or more images of one or more products residing on a product storage location from an image capturing device. Based on the received images, one or more computer processors determine a count of the one or more products. One or more computer processors determine a confidence in the count of the one or more products. In response to determining the confidence is below a threshold, one or more computer processors calculate a recommended position of the image capturing device to produce an improved image of the one or more products. One or more computer processors transmit instructions to the image capturing device to move to the recommended position. One or more computer processors determine whether the image capturing device is in the recommended position.

GRAIN MEASURING DEVICE, COMBINE, FIELD MANAGEMENT SYSTEM

A grain measuring device includes a reaping determination unit in a combine harvester to determine a state of reaping grains; and a measurement unit configured to measure a component of the grains and save a result of measurement when the reaping determination unit determines that the combine harvester is in in the state of reaping the grains.

Method and system for optical yield measurement of a standing crop in a field

An data processor is configured to identify the component pixels of a harvestable plant component within an obtained image data of plant pixels of the one or more target plants. An edge, boundary or outline of the component pixels is determined. The data processor is configured to detect a size of the harvestable plant component based on the determined edge, boundary or outline of the identified component pixels, along with an adjustment based on analysis of any exposed portions of the harvestable plant component. A user interface is configured to provide a yield indicator based on the detected size of the harvestable plant component.

PROCESSING APPARATUS, AND PROCESSING METHOD

This invention provides a processing apparatus () including a container identification score computation unit () that computes an identification score of a container for a product, based on an image to be processed containing the product, a product identification score computation unit () that computes an identification score of the product, based on the image to be processed, and a first identification unit () that decides identification information of the product, based on the computed identification score of the container and the computed identification score of the product.

Commodity reading apparatus, commodity sales data processing apparatus and commodity reading method

In accordance with one embodiment, a determination unit configured to determine whether or not the object discriminated by the discrimination unit passes through a second area specified different from a first area in a frame range during movement of the object to the first area specified in the frame range of the animation, a first recognition unit configured to recognize a candidate commodity as a candidate of a sales commodity based on a feature amount appeared on the object in the first area if the determination unit determines that the object passes through the second area, and a second recognition unit configured to recognize a commodity data represented by an optical mark on the object in the first area if the determination unit determines that the object does not pass through the second area.

METHODS OF YIELD ASSESSMENT WITH CROP PHOTOMETRY

A method of evaluating one or more kernels of an ear of maize using digital imagery that includes acquiring a digital image of the one or more kernels of the ear of maize without the use of spatial reference points, processing the digital image to estimate at least one physical property of the one or more kernels of the ear of maize from the digital image, and evaluating the at least one kernel of maize using the estimate of the at least one physical property of the at least one kernel of maize. The method includes using one or more such digital images to estimate yield on a plant, management zone, field, county and country level. 1. A method of predicting total yield of a corn crop , comprising:obtaining a plurality of images of an ear of corn without the use of spatial reference points,determining the number of kernels per ear, andcalculating predicted total yield or test weight based on the image, wherein the predicted total yield or test weight is calculated based on an estimate of the number of total ears in the area of the predicted total yield or test weight, which number of total ears is based on one or more of as-planted data, historical information about the variety planted, an aerial image of the plants, rainfall or crop moisture data.2. The method of claim 1 , wherein an image of the corn ear is positioned within a target window on the viewing screen of an imaging device.3. The method of claim 2 , wherein the plurality of images are still images from a video feed of the corn ear.4. The method of claim 2 , wherein the images are selected based on having a corn ear to target window surface area ratio between 70% to 90%.5. The method of claim 4 , wherein the corn kernels on the corn ear are segmented and counted.6. The method of claim 1 , wherein the number of kernels per ear is the median number of kernels from a set of still images.7. The method of claim 1 , wherein the image is a two dimensional image and the total number of kernels per ear is obtained ...

METHOD AND APPARATUS FOR VIDEO CODING

Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes receiving circuitry and processing circuitry. For example, the processing circuitry decodes prediction information of a current block in a current picture from a coded video bitstream. The prediction information is indicative of a prediction mode that uses a first optical flow refinement coding tool. The first optical flow refinement coding tool uses a grid structure that is used additionally by at least a second optical flow refinement coding tool during operations of optical flow refinement. Then, the processing circuitry calculates, using the first optical flow refinement coding tool, refinements to predictions of samples of the current block based on the grid structure, and reconstructs the samples of the current block based on the refinements and the predictions of the samples. 1. A method for video encoding , comprising:receiving samples of a current block in a current picture;determining, by processing circuitry for coding the current block, a prediction mode that uses a selected optical flow refinement coding tool, from candidate tools implemented by the encoder including a bi-directional optical flow (BDOF) based coding tool and an affine prediction refinement with optical flow (PROF) based coding tool;encoding the samples of the current block according to the prediction mode to obtain encoded data, the encoding including calculating, by the processing circuitry and using the selected optical flow refinement coding tool in units of sub-blocks of the current block, refinements to predictions of the samples of the current block regardless of the selected optical flow refinement coding tool being the BDOF based coding tool or the PROF based coding tool, each sub-block of the sub-blocks having a unified sub-block size for the BDOF based coding tool and the PROF based coding tool; andgenerating a coded video bitstream, ...

AN APPARATUS AND METHOD FOR PERFORMING IMAGE-BASED DISH RECOGNITION

There is provided a computer-implemented method for performing image-based dish recognition. The method includes acquiring a first image depicting a dish to be recognized, analyzing the first image using a predictive model to determine a first candidate theme, and acquiring a reference set of dish identifiers. The method further includes calculating, for each of the dish identifiers in the reference set, an association score indicative of a degree of similarity between the dish represented by the respective dish identifier and the first candidate theme, selecting one or more dish identifiers in the reference set having the highest association scores as one or more variant dish identifiers of the first candidate theme, and outputting a centroid dish identifier of the first candidate theme and the one or more variant dish identifiers of the first candidate theme. 1. A computer-implemented method for performing image-based dish recognition , the method comprising:acquiring a first image depicting a dish to be recognized;analyzing the first image using a predictive model to determine a first candidate theme, wherein the first candidate theme comprises a plurality of candidate dish identifiers each associated with a candidate dish, one of the plurality of candidate dish identifiers being a centroid dish identifier associated with a candidate dish most representative of the first candidate theme;acquiring a reference set of dish identifiers;calculating, for each of the dish identifiers in the reference set, an association score indicative of a degree of similarity between the dish represented by the respective dish identifier and the first candidate theme based on a proximity distance between a vector representing the respective dish identifier in the reference set and a vector representing the first candidate theme, or based on an angle between a vector representing the respective dish identifier in the reference set and a vector representing the first candidate theme, ...

Method of using, apparatus, product, and system for a no touch point-of-sale self-checkout

A method, computer program product, and system to perform a sale transaction are provided. The method includes identifying each item of a plurality of items, based on at least one image of the plurality of items, determining a cost for each item, optionally identifying a person based on an image of the person, adding each of the items and each of the costs to a sale transaction, and charging the person for the sale transaction.

Method, computer program product, and system for providing a sensor-based environment

Method, computer program product, and system to influence a person within an environment having a plurality of items for selection. The method includes capturing, using a first visual sensor disposed within the environment, field of view information for the person, performing analysis on the field of view information using a computing device, and identifying, based on the analysis, one or more first items of the plurality of items that are included within the field of view of the person. The method further includes selecting, based on the identified one or more items, at least one second item of the plurality of items for presentation to the person; and presenting information related to the at least one second item to the person.

Methods and systems for identifying internal conditions in juvenile fish through non-invasive means

Methods and systems are disclosed for improvements in aquaculture that allow for increasing the number and harvesting efficiency of fish in an aquaculture setting by identifying and predicting internal conditions of the juvenile fish based on external characteristics that are imaged through non-invasive means.

Method and Apparatus for Automated Plant Necrosis

A method of real-time plant selection and removal from a plant field including capturing a first image of a first section of the plant field, segmenting the first image into regions indicative of individual plants within the first section, selecting the optimal plants for retention from the first image based on the first image and the previously thinned plant field sections, sending instructions to the plant removal mechanism for removal of the plants corresponding to the unselected regions of the first image from the second section before the machine passes the unselected regions, and repeating the aforementioned steps for a second section of the plant field adjacent the first section in the direction of machine travel.

Work assistance system, kitchen assistance system, work assisting method, and non-transitive computer-readable medium recording program

The work assistance system assists work including a plurality of steps. The work assistance system includes a determination unit and an announcement control unit. The determination unit determines, based on an image of a working area, whether a working result of a determination target step of the plurality of steps is acceptable or unacceptable. The announcement control unit orders an announcement unit to perform announcement operation when the working result of the determination target step has been determined to be unacceptable by the determination unit.

Information processing apparatus, information processing method, and storage medium

An estimation parameter for estimating the actual number of target objects in a designated region of a field is learned using a feature amount acquired from a captured image of a set region of the field and the actual number of target objects in the set region as learning data.

Camera-enabled machine learning for device control in a kitchen environment

A cooking control system accesses a set of training data used to train a machine learned model configured to detect smoke in a kitchen environment based on image data of a stovetop. The cooking control system receives real-time image data of a stovetop from a camera in the kitchen environment and applies the machine learned model to the image data to determine a likelihood that the image data includes smoke. If the cooking control system determines that the received images contain smoke, the cooking control system may perform one or more actions, such as disabling operation of the stovetop and sending an alert indicative of smoke to a user of he cooking control system or a local emergency department.

System, device, process and method of measuring food, food consumption and food waste

The system, device, process and method of measuring food, food consumption and waste with image recognition and sensor technology is presented to empower cafeterias, processors, quick service restaurants, and other institutions and locations to reduce food waste. Using kitchen and consumer data, the system allows food providers to characterize key food properties, optimize portion sizing, ingredient combinations, and meal preparation, to maximize profits and minimize excess. The current system, process and method optimize the food chain uses analytics and prediction insights. Gathering data through the use of a sensor package (typically including a camera system), and/or smartphone application, a digital platform is then used to give insights to institutions over time. This feedback includes food supplier changes, quality reports, preparation changes, portion sizing, ingredient usage, and customer feedback.

Object throughput using trained machine learning models

Disclosed are techniques for determining object throughput. A method may include obtaining first data representing a first image corresponding to a first time, identifying a first portion of the first data that depicts a first object at a first location, obtaining second data representing a second image corresponding to a second time, identifying a second portion of the second data that depicts the first object at a second location, obtaining third data indicating a counting threshold, determining based at least on the third data and the second location, that the first object satisfies the counting threshold, generating a value indicating a number of objects satisfying the counting threshold, the number of objects including the first object, generating a data value indicating a throughput of the number of objects based on the value indicating the number of objects satisfying the counting threshold and elapsed time between the first and second times.

Consumable personalization

Systems and methods for consumable personalization are provided. In example embodiments, a request to identify similar consumables that are similar to a first consumable is received from a user device of a user. Consumable data corresponding to a plurality of consumables is accessed. The consumable data includes attributes of respective consumables of the plurality of consumables. The attributes include potency data for a first active ingredient. A second consumable among the plurality of consumables is identified by comparing attributes of the first consumable with the attributes of the respective consumables of the plurality of consumables. The second consumable is presented on a user interface of the user device of the user.

Meal Planning Menu Proposal System

[Problem] To provide a system in which candidates for breakfast, lunch, and dinner can be visually attractively expressed, and when wanting to change lunch while adopting breakfast and dinner, only a candidate for lunch can be changed to the next candidate while being visually attractively expressed. [Solution] This dish menu proposal system, which displays a dish menu proposal on a screen which is a touch panel, has: a dish storage unit that stores a plurality of dishes and a plurality of dish images; a menu proposal unit that proposes two or more menus for breakfast, lunch, and dinner, respectively; a menu display unit that displays, on a breakfast display section, a lunch display section, and a dinner display section on the screen, menu images for the breakfast, lunch, and dinner; and a menu update display unit that when a slide input has been performed on any among the breakfast display section, the lunch display section, and the dinner display section, slides the slide-input menu image for the breakfast, lunch, or dinner on a second menu image pertaining to a second menu. 1. A meal planning menu proposal system for displaying a proposal for a meal planning menu on a screen as a touch panel , the meal planning menu proposal system comprising:a dish storage unit configured to store a plurality of dishes and images of the plurality of dishes;a menu proposal unit configured to propose two or more menus for each of breakfast, lunch, and dinner, the two or more menus including a first menu and a second menu, the second menu being a menu for a same day as the first menu and being different from the first menu;a menu display unit configured to read out images of dishes included in the first menus of the breakfast, lunch, and dinner menus from the dish storage unit, and simultaneously display the images in a breakfast display section, a lunch display section, and a dinner display section on the screen as menu images for breakfast, lunch, and dinner, respectively; anda ...

MULTI-ZONE PROCESS AND APPARATUS FOR TREATING WASTEWATER

Wastewater containing organic matter may be treated using a multi-zone apparatus. In a first zone, organic matter in the wastewater may, among other things, be converted to at least volatile fatty acids (VFAs) and, thereafter, a portion of the treated wastewater may flow to a second zone that may, among other things, convert the VFAs to methane. 1. An apparatus for treating wastewater comprising:a first zone adapted to receive a mixed stream comprising previous, anaerobically treated wastewater from a second zone, wherein the previous, anaerobically treated wastewater facilitates direct transport and passage of one or more second biological microbes from the second zone to the first zone, said first zone comprising a first bioreaction zone, wherein the first bioreaction zone is configured with one or more retaining or facilitating structures that retain or facilitate growth of one or more first biological microbes and convert organic matter in the first liquid stream into at least carbon dioxide to produce treated wastewater;a second zone adapted to receive the treated wastewater from the first zone, said second zone comprising a second bioreaction zone comprising a plurality of anaerobically facilitating structures configured to anaerobically facilitate growth of one or more second biological microbes; andwherein said plurality of anaerobically facilitating structures comprise a pair of electrodes comprising both an anode and a cathode configured to further treat the wastewater and at least convert the carbon dioxide into methane.2. The apparatus as in wherein the first and second zone are configured in the same vessel.3. The apparatus as in wherein the first and second zones are configured in different vessels.4. The apparatus as in further comprising first means for mixing or fluidizing biomass or dynamic media structures in the first zone.5. The apparatus as in wherein the first means for mixing or fluidizing comprises means selected from the group comprising a ...

Refrigeration appliance comprising a camera module

A refrigeration appliance includes a camera module for detecting first image data of an item to be refrigerated at a first time point and second image data of the item to be refrigerated at a second time point. A freshness determination device is provided for determining the state of freshness of the item to be refrigerated based on the first image data and the second image data.

Generating customized alerts with computer vision and machine learning

Systems and methods are disclosed that enable more accurately generating customized alerts with computer vision (CV) and machine learning (ML), based on features extracted from collected imagery, when the features have contextual or situational significance. For example, a CV platform monitoring container content levels may generate an alert that may include placing a shopping cart entry or providing a purchase recommendation. Accompanying ML capability can leverage the CV historical data to improve container content and level determinations, and also adjust a consumption pattern threshold used as a trigger.

Process and system for in-line inspection of product stream for detection of foreign objects

A process for detecting foreign objects in a food-containing product stream comprises: forwarding the product stream, illuminating the product stream, generating raw data based on electromagnetic energy reflected from the product stream using a camera, and processing the raw data to generate classified image data corresponding with food product, foreign object(s), and background. A system for detecting foreign objects in the product stream comprises a forwarding device, an illuminator, a camera, and instructions in memory that form image data and classify the data as corresponding with food product, foreign objects, and background.

METHOD FOR OPERATING A COOKING APPLIANCE, AND COOKING APPLIANCE

A method for operating a cooking appliance having at least one cooking chamber for preparing food includes detecting high-frequency data during a cooking process using at least one high-frequency measuring system. The method further includes deriving at least one cooking parameter characterizing the food from the high-frequency data using at least one processing system. The high-frequency data is processed using at least one self-learning model of machine learning stored in the processing device. The processing device independently derives the cooking parameter from the high-frequency data via the model. 1. A method for operating a cooking appliance having at least one cooking chamber for preparing food , comprising:detecting high-frequency data during a cooking process using at least one high-frequency measuring system, andderiving at least one cooking parameter characterizing the food from the high-frequency data using at least one processing device,wherein the high-frequency data is processed using at least one self-learning model of machine learning stored in the processing device, and the processing device independently derives the at least one cooking parameter from the high-frequency data via the at least one model.2. The method according to claim 1 , wherein the high-frequency measuring system detects reflection spectra of the cooking chamber and/or of the food claim 1 , and the high-frequency data is calculated from the reflection spectra claim 1 , and/or the high-frequency data is the reflection spectra.3. The method according to claim 1 , wherein the at least one self-learning model is created or trained by supervised machine learning; wherein at least one data set of a representative set of cooking processes is detected as a reference; wherein at least one association of high-frequency data with the at least one cooking parameter is included as a target variable for learning in the at least one data set; and wherein correlations between the high- ...

Detection Method and Device Thereof

This invention provides a detection method and a device thereof which are applied to the field of image processing. The method includes: receiving an image of a target object, acquiring a type of the target object according to a first classifier and the image of the target object, and sending information containing the type of the target object to a display device. The method can automatically prompt a product type, thereby reducing the time of manual recognition and increasing the accuracy of the recognition.

METHOD AND DEVICE FOR AUTOMATICALLY COOKING FOOD

The present application relates to a method for automatically cooking food, and the method comprises acquiring an initial image of at least one food ingredient, the initial image being acquired before cooking or when the cooking is not complete; processing the initial image to extract characteristic parameters of at least one food ingredient, wherein the characteristic parameters of the food ingredient indicates the cooking characteristics of the food ingredient; determining cooking condition parameters for at least one food ingredient based on characteristic parameters of at least one food ingredient. 1. A method for automatically cooking food , comprising:acquiring an initial image of a variety of food ingredients in a cooking container, the initial image being acquired before cooking or when the cooking is not complete;acquiring an intermediate image of the variety of food ingredients in the cooking container after a predetermined time interval;processing the initial image and the intermediate image to extract characteristic parameters of the food ingredients, and the characteristic parameters of the food ingredients indicate the cooking characteristics of the food ingredients;determining cooking condition parameters for the variety of food ingredients based on characteristic parameters of the food ingredients;wherein, the processing of the initial image and the intermediate image to extract the characteristic parameters of the food ingredients comprises:respectively determining doneness speed of at least two kind of food ingredients among the variety of food ingredients based on the initial image and intermediate image.2. (canceled)3. (canceled)4. (canceled)5. (canceled)6. The method according to claim 1 , wherein the determination of the cooking condition parameters for the variety of food ingredients based on the characteristic parameters of the food ingredients comprises:comparing the characteristic parameters of the food ingredients with a first specified ...

Image-Based Drive-Thru Management System

The subject matter of this specification can be implemented in, among other things, methods, systems, computer-readable storage medium. A method can include receiving, by a processing device, image data including one or more image frames indicative of a current state of a drive-thru area. The processing device determines a vehicle disposed within the drive-thru area based on the image data. The processing device receives order data with a pending meal order. The processing device determines a first association between the vehicle and the pending meal order based on the image data. The processing devices determine a meal delivery procedure associated with the based on the association between the vehicle and the pending meal order. The processing device performs may perform the meal delivery procedure. The processing device may provide the meal delivery procedure for display on a graphical user interface (GUI). 1. A method , comprising:receiving, by a processing device, image data comprising one or more image frames indicative of a state of a drive-thru area;determining, by the processing device, a vehicle disposed within the drive-thru area based on the image data;receiving, by the processing device, order data indicative of a pending meal order;determining, by the processing device, a first association between the vehicle and the pending meal order based on the image data;determining, by the processing device, from a plurality of meal delivery areas, a first meal delivery area associated with the vehicle based on the first association; andperforming, by the processing device, at least one of a) causing performance of a meal delivery procedure using the first meal delivery area or b) communicating a notification associated with the first meal delivery area.2. The method of claim 1 , further comprising:determining a visual vehicle identifier corresponding to the vehicle disposed within the drive-thru area based on the image data;determining a menu display update based ...

IMAGE-BASED KITCHEN TRACKING SYSTEM WITH DYNAMIC LABELING MANAGEMENT

The subject matter of this specification can be implemented in, among other things, methods, systems, computer-readable storage medium. A method can include receiving, by a processing device, image data having one or more image frames indicative of a state of a meal preparation area. The method may further include, determining, based on the image data, a first feature characterization of a first meal preparation item associated with the state of the meal preparation area. The method may further include determining that the first feature characterization does not meet object classification criteria for a set of object classifications. The method may further include causing a notification indicating the first meal preparation item and one of an object classification or a classification status corresponding to the first meal preparation item on a graphical user interface (GUI). 1. A method , comprising:receiving, by a processing device, image data comprising one or more image frames indicative of a state of a meal preparation area;determining, by the processing device based on the image data, a first feature characterization of a first meal preparation item associated with the state of the meal preparation area;determining, by the processing device, that the first feature characterization does not meet object classification criteria for a set of object classifications; andcausing, by the processing device, a notification indicating the first meal preparation item and one of an object classification or a classification status corresponding to the first meal preparation item on a graphical user interface (GUI).2. The method of claim 1 , wherein determining the first feature characterization comprises:using the image data as input to a machine learning model; andobtaining one or more outputs of the machine learning model, the one or more outputs indicative of the first feature characterization.3. The method of claim 1 , further comprisingdetermining, by the processing ...

System and Method for Recipe to Image Associations

System and method for associating images to recipe records. In one embodiment, a method is provided which includes: receiving an uploaded photograph of a recipe image; and searching a database for an image which matches to the uploaded image. The database search may, in one embodiment, make use of a convolutional neural network (CNN)-based classifier. When one of the records in the database is identified as matching, providing a portion of the data associated to the record to the user device; receiving feedback from the user; and based on the feedback, providing a remaining portion of the data associated to the identified record to the user device for logging thereat; or enabling the user to create a new consumable item record.

System and method for estimating a harvest volume in a vineyard operation

Some embodiments are related to a system for estimating a harvest volume in a vineyard operation organized into rows of vine stocks, including: a photographic device for capturing a photographic image of a set of stocks when the system passes between two rows of the vineyard operation; a device for measuring a distance between the vine stocks and the photographic device; and a calculator for detecting the berries within the photographic image, determining a number of berries in a bunch, determining a number of bunches on a stock, and determining an indicator of the volume depending on the number of berries in a bunch, the number of bunches on a stock and the diameter of the berries determined from the photographic image and the distance measurement.

Monitoring shelves with pressure and light sensors

A system for monitoring planogram compliance on a store shelf is disclosed. The system may include a plurality of detection sensors and a processor. The processor may be configured to receive first signals from a first subset of detection sensors after a plurality of products are placed on the store shelf, and use the first signals to identify at least one pattern associated with a product type of the products. The processor may further be configured to receive from a second subset of detection sensors second signals indicative of no products being placed on at least one area of the store shelf, and use the second signals to determine at least one empty space on the store shelf. The processor may also be configured to determine, based on the at least one pattern and the at least one empty space, at least one aspect of planogram compliance.

Systems for Nutritional Monitoring and Management

This invention is a system for nutritional monitoring and management which includes a camera, a spectroscopic sensor, a fiducial component, a wearable biometric sensor, a smart utensil or dish, a passive feedback mechanism which provides a person with information concerning food item types and/or quantities, and an active stimulus mechanism which modifies the person's food-related physiological processes. This system can help a person to improve their dietary habits and health.

Device and Method for Optical Quality Control of the Coating or Staining of a Kernel-Type Substrate

The invention relates to a device and a method for optical quality control of the coating or staining of a kernel-type substrate, in particular seed with a colour and contrast intensive coating composition.

COOKING APPARATUS AND CONTROLLING METHOD THEREOF

A cooking apparatus including an image capturer and a processor configured to identify a food object from a plurality of images obtained through the image capturer, adjust a capture interval at which an image of the food object is obtained in real time through the image capturer based on information about a cooking state change of the identified food object, and generate a video based on the captured image obtained according to the adjusted capture interval. 1. A cooking apparatus comprising:an image capturer; anda processor configured to:identify a food object from a plurality of images obtained through the image capturer,adjust a capture interval at which an image of the food object is obtained in real time through the image capturer based on information about a cooking state change of the identified food object, andgenerate a video based on the image obtained according to the adjusted capture interval.2. The cooking apparatus of claim 1 , wherein the information about the cooking state change comprises a cooking state change amount claim 1 , andwherein the processor is further configured to adjust the capture interval to be inverse-proportional with the cooking state change amount of the food object.3. The cooking apparatus of claim 2 , wherein the processor is further configured to:based on the cooking state change amount of the food object being less than a first threshold value, increase the capture interval of the image capturer, andbased on the cooking state change amount of the food object being greater than or equal to a second threshold value, decrease the capture interval of the image capturer.4. The cooking apparatus of claim 2 , wherein the processor is further configured to:analyze the food object using at least one feature information from the plurality of images obtained, andadjust a number of the at least one feature information to be proportional with the cooking state change amount of the food object.5. The cooking apparatus of claim 4 , wherein ...

Fishing System for Fishing for Shrimps, Fish Processing Line and Vessel Provided Therewith, and Method Therefor

The invention relates to a fishing system ( 102 ), a fish processing line ( 18, 22 ) and/or vessel ( 2 ) provided therewith, and a method ( 26 ) therefor. The fishing system ( 102 ) according to the invention comprises a fishing net ( 6 ) for catching shrimps or fish; transfer means ( 14, 15, 16 ) connected operatively to the fishing net ( 6 ) for bringing on board the caught shrimps or fish; an automatic detection device ( 18 ) configured to detect, classify and if desired sort the shrimps or fish brought on board; a registration system ( 104 ) connected operatively to the detection device ( 18 ) and configured to receive, store and read and/or transmit data ( 108 ) obtained with the detection device ( 18 ) about the shrimps or fish brought on board, wherein the data ( 108 ) comprise information about the quantity, classification and location of the caught shrimps or fish.

Method and apparatus for image analysis

An electronic device comprising: a memory; a communication circuit; and at least one processor operatively coupled to the memory and the communication circuit, configured to: obtain a first image; extract a feature associated with an object depicted in the first image; and control the communication circuit to transmit an indication of the feature to a server; and receive analysis information associated with the object from the server through the communication circuit.

Image-based food analysis for medical condition warnings

A method of performing image based analysis of food. The method includes receiving, with an electronic processor, image data captured by an image capture device, analyzing the image data to identify a food represented in the image data, and determining a characteristic of the food identified in the image data. The method further includes accessing medical information of a user, determining a level of risk associated with the user ingesting the food identified in the image data based on the medical information of the user, and outputting a notification, where the notification providing information related to the level of risk associated with the user ingesting the food identified in the image data.

Food Inventory System and Method

A food inventory system, including a portable device which may include a bar code scanner and camera to add and remove inventory items to and from the inventory. The scanner may be mounted on an inventory storage container to facilitate inventory control from one or more domestic storage devices, including refrigerators, freezers, and pantries. The inventory system may display a table listing the inventory items along with variable details. Based on the food inventory list, the inventory system may suggest recipes, display the ingredients in stock for suggested recipes, and create a shopping list of the ingredients not in stock for a desired recipe. The portable device may be configured with wireless capability, connection to the internet, phones, tablets, laptops, and personal computer.

Restaurant-specific food logging from images

A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Interactive touch screen device for wine

Interactive display and rendering device, system and method for wine bottles are disclosed. An interactive wine management and display device and method using a scanning instrument capable of scanning information regarding a bottle of wine; an imaging instrument capable of collecting an image of at least a portion of a bottle of wine; a connection to a wine database containing information regarding wines; a connection to a database having images of wine bottles. The device is able to render the images as well as information on the wine to a display for user interaction.

Detecting objects in images

A system trains a computer model to classify images and to draw bounding boxes around classified objects in the images. The system uses a combination of partially labeled training images and fully labeled training images to train a model, such as a neural network model. The fully labeled training images include a classification label indicating a class of object depicted in the image, and bounding box or coordinate labels indicating a number of objects of the class in the image as well as the location of the objects of the class in the image. The partially labeled training images include a classification label but no indication of where in the image any objects of the class are located. Training the model using both types of training data makes it possible for the model to recognize and locate objects of classes that lack available fully labeled training data.

Inspecting store shelf capacity

A system for processing images captured in a retail store is provided. The system may comprise at least one processor configured receive at least one image depicting part of at least one store shelf having a plurality of products displayed thereon, the plurality of products including a group of first products associated with a first product size and a group of second products associated with a second product size, analyze the at least one image to detect the plurality of products, identify one or more vacant spaces associated with the plurality of products, determine that by rearranging the group of second products to partially eliminate the one or more identified vacant spaces, at least one additional first product may be displayed on the at least one store shelf next to the group of first products, and provide information to a user indicative of the identified vacant spaces.

Article recognition apparatus and article recognition method

According to one embodiment, an article recognition apparatus includes an image interface and a processor. The image interface acquires an image captured by photographing a predetermined place where a plurality of articles are disposed. The processor acquires a first image through the image interface, acquires a second image through the image interface after detecting a predetermined event, and recognizes an article, based on an image of an article area of an article which is absent in the second image, among article areas extracted from the first image.

An Apparatus and Method for Identifying Plant Varieties from Leaf Samples Taken Whilst in the Field

An apparatus for identifying plant varieties from leaf or flower samples taken whilst in the field comprises a scanning device having a backlight so as to enable a detailed image of a sample to be recorded digitally, a computer for uploading the image for analysis, a computer program which allocates user prescribed parameters such as leaf venation, leaf shape, base position and shape and leaf curvature to the image, and utilising the data produced by the computer program and applying an algorithm to it for matching the data against a database of plant varieties to determine the highest match probability.

Waste analysis system and method

Embodiments of the present invention provide techniques for identifying and quantifying waste in a process. Waste information is input via images and/or natural language. The amount of waste is estimated based on information in images and/or a natural language description. A computer-implemented technique extracts metadata on waste products from the images and/or natural language description. A variety of factors such as social media trends, weather, traffic, and/or sports schedules are evaluated by the computer and used in predicting the amount of waste that will occur.

System and method for determination of unusable products

A credibility weight for each of a plurality of users is stored and is associated with a reliability of the user in accurately indicating whether the products have become spoiled. Images of a plurality of products at a retail store are received and electronically arranged in an organized pattern. The organized pattern is rendered onto selected ones of a plurality of display devices. Electronic choices from selected ones of the plurality of the users are received. Each of the electronic choices indicates for a selected one of the plurality of products whether the selected user believes the selected product has spoiled or has become unusable. A spoilage score for each product of the products is determined. A control signal is transmitted to a receiver circuit at the retail store instructing a human or robot to perform an investigation when the spoilage score exceeds a predetermined threshold.

Image-based spoilage sensing refrigerator

Disclosed are various embodiments for determining whether food in a refrigerator has spoiled. An application executing on a computing device receives an image from a refrigerator of a compartment of the refrigerator. The application then analyzes the image to identify a food item in the image. Subsequently, the application analyzes the image to identify a potentially spoiled area of the food item. The application then compares the potentially spoiled area of the food item to a model of a spoiled food item. Afterwards, the application determines that the identified food item has spoiled based at least in part on a comparison of the potentially spoiled area of the identified food item to the model of the spoiled food item.

Methods and systems for inspecting plants for contamination

A method of inspecting plants for contamination includes generating a first series of images of a plant using a camera mounted to a frame being moved along a planting bed by a harvester, identifying a region of interest displayed in the first series of images as a region of contamination on the plant based on a color criterion and a morphological criterion applied to the region of interest, and transmitting data including an instruction to increase a vertical distance between the plant and a cutter of the harvester to avoid harvesting the plant in response to identifying the region of interest as the region of contamination. The method further includes generating a second series of images of an additional plant as the frame continues to be moved along the planting bed by the harvester while the vertical distance between the plant and the cutter is being increased.

Consumable personalization

Systems and methods for consumable personalization are provided. In example embodiments, a request to identify similar consumables that are similar to a first consumable is received from a user device of a user. Consumable data corresponding to a plurality of consumables is accessed. The consumable data includes attributes of respective consumables of the plurality of consumables. The attributes include potency data for a first active ingredient. A second consumable among the plurality of consumables is identified by comparing attributes of the first consumable with the attributes of the respective consumables of the plurality of consumables. The second consumable is presented on a user interface of the user device of the user.

Augmented reality virtual order assistant

An approach is provided for generating an interface. Using natural language processing and natural language understanding, ingredients are derived from audio data from a customer's spoken order of ingredients of a food item. Locations of the ingredients in a preparation area are identified. A location of an employee is determined. Distances of the ingredient locations to the employee location are calculated. A sequence of selecting the ingredients is determined so that the employee selecting the ingredients in the sequence optimizes a speed at which the food item is prepared. An overlay to an interface for viewing in an augmented reality (AR) headset worn by the employee is generated and displayed. The overlay includes indicators overlaying an image of the preparation area. The indicators mark the ingredients, mark the sequence of selecting the ingredients, and distinguish the ingredients from other ingredients in the preparation area.

Method for controlling operation of refrigerator by using speech recognition, and refrigerator employing same

A refrigerator according to one embodiment of the present invention includes: a memory for storing information on food stored in a storeroom; a weight detecting unit disposed in the storeroom for detecting the weight of the food in order to determine whether food is received or withdrawn; a controller for creating a request for confirmation information on the received or withdrawn food when the food is determined to have been received or withdrawn; a speech output unit for outputting the request created by the controller as speech; and a speech input unit for receiving the response to the output request as speech, wherein the controller analyzes the response and updates information on the food stored in the storeroom.

Pos terminal device, commodity recognition method, and non-transitory computer readable medium storing program

A POS terminal device capable of improving a recognition rate in a process for recognizing a commodity irrespective of the surrounding environment is provided. A POS terminal device ( 1 ) includes a brightness measurement unit ( 2 ), an irradiation unit ( 4 ), an image pickup unit ( 6 ), and a recognition process unit ( 8 ). The brightness measurement unit ( 2 ) measures the brightness of environmental light around the POS terminal device ( 1 ). The irradiation unit ( 4 ) irradiates a commodity with light, the light being adjusted according to the brightness of the environmental light measured by the brightness measurement unit ( 2 ). The image pickup unit ( 6 ) shoots the commodity irradiated with the light by the irradiation unit ( 4 ) and thereby generates an image thereof. The recognition process unit ( 8 ) performs a process for recognizing the commodity based on the image generated by the shooting performed by the image-pickup unit ( 6 ).

Mobile terminal and operation method thereof

An operation method of a mobile terminal according to an embodiment of the present invention comprises the steps of displaying a first preview image including a food item through a camera provided in the mobile terminal; receiving an input designating an area occupied by the food item; obtaining calories of the food item in response to the received input; and displaying the obtained calories of the food item on one side of the food item.

Commodity sales data processing apparatus and control program

A commodity sales data processing apparatus registers, if a code obtained by a receiver is a first code for identifying a commodity, sales data of the commodity identified by the first code. The apparatus acquires, if the code input by the receiver is a second code for identifying a commodity group ordered via a network, data of the commodity group identified by the second code from a saving destination where data of ordered commodities is saved. The apparatus registers, based on the data acquired from the saving destination, sales data of a commodity included in the commodity group identified by the second code. The apparatus executes settlement processing based on the sales data of the commodity identified by the first code and the commodity included in the commodity group identified by the second code.

Realogram to Planogram User Interface

A system and method that generates a planogram from a realogram is disclosed. The method includes receiving, from an image processing module, a realogram, the realogram including an image and information about a set of items recognized in the image, determining one or more linear groupings of a subset of the set of recognized items corresponding to each shelf, generating a planogram based on the realogram and the one or more linear groupings, generating a user interface for presentation on a client device of a user, presenting the realogram in a first portion of the user interface and the planogram in a second portion of the user interface, receiving user input via the user interface, and updating the planogram based on the user input.

Image filter based on row identification

System and techniques for an image filter based on row identification are described herein. A crop row center represented in an image of a crop row can be calculated. A filter corresponding to a set of expected crop characteristics of the crop row can be obtained. Elements in the image can then be categorized based on applying the filter to the image when the filter anchored on the crop row.

Object image recognition and instant active response with enhanced application and utility

A device for detecting and marking ticks and tick bites on a body or limb. The device has an image capturing device that is in communication with image recognition software. Images of skin are analyzed to detect objects consistent with ticks or tick bites. Once such object is detected, the device automatically disperses a marking material in the proximity of the detected tick or tick bite.

Vision-based system for acquiring crop residue data and related calibration methods

A method for calibrating crop residue data for a field acquired using a vision-based system may include receiving image data associated with an imaged portion of the field, analyzing the image data using a first residue-estimating technique to determine a first estimated value of a crop residue parameter for the imaged portion of the field, and analyzing the image data using a second residue-estimating technique to determine a second estimated value of the crop residue parameter for the imaged portion of the field. In addition, when a differential exists between the first and second estimated values, the method may also include adjusting at least one of the first estimated value or one or more additional estimated values of the crop residue parameter determined using the first residue-estimating technique based on at least one of the second estimated value or the differential between first and second estimated values.

Product recognition apparatus, sales data processing apparatus, and control method

According to the embodiment, a product recognition apparatus includes a shooting device, a display, and a processor. The aforementioned processor controls the display so that a frame image of an object shot by the shooting device is displayed in an image display region of the display. Also, the processor controls the display so that a location image illustrating the location of the object is displayed so as to overlap the frame image in the image display region of the display.

Multi-sensor array including an ir camera as part of an automated kitchen assistant system for recognizing and preparing food and related methods

An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.

User terminal apparatus and control method thereof

A user terminal apparatus is provided. The user terminal apparatus includes a camera configured to obtain a captured image; a storage configured to store a food intake history; a processor configured to extract a food image from the captured image and determine a food type of a food item included in the captured image based on feature information of the extracted food image and the previously stored food intake history; and a display configured to display relevant information about the determined food type.

Object recognition device, checkout terminal, and method for processing information

An object recognition device includes an operation unit configured to receive a user input about an item, a storage unit that stores image data of the item, an imaging unit configured to acquire an image of the item and generate image data therefrom, and a control unit configured to compare the generated image data with the stored image data, and cause information about updating the stored image data to be presented to a user, based on a comparison result.

Verfahren und Anordnung zur optischen Beurteilung von Erntegut in einer Erntemaschine

Ein Verfahren und eine Anordnung zur optischen Beurteilung von Erntegut arbeiten nach folgenden Schritten: Aufnehmen eines Bildes des Ernteguts (62) mit einer Kamera (66); Identifizieren von Einzelobjekten in dem Bild mittels eines elektronischen Bildverarbeitungssystems (80); Klassifizieren der Einzelobjekte in vorbestimmte Objektklassen anhand eines Vergleichs von Farb- und/oder Kontur- und/oder Texturmerkmalen der Einzelobjekte mit entsprechenden Eigenschaften von in einer Datenbank (78) abgelegten Referenzobjekten mittels des Bildverarbeitungssystems (80); und Bestimmen der absoluten oder relativen Anzahlen oder Flächen der den jeweiligen Objektklassen zugeordneten Einzelobjekte.

Load-based yield sensor

A method of estimating the mass of crop entering into a grain tank on a harvesting machine, comprising the steps of mounting a load sensor on the upper bearing of a conveyor belt moving crop through the clean grain elevator into the grain tank, connecting the load sensor to a processor, using the load sensor to measure a load on the conveyor belt when no crop is present in the clean grain elevator, and also when crop is moving through the clean grain elevator, and comparing the load with no crop present to the load when crop is present to estimate the mass of crop moving through the clean grain elevator.

Grain quality sensor

A grain quality sensor comprising a photosite array, an illumination source, a filter, and an electronics module, wherein the illumination source directs light onto a crop sample, wherein the filter limits passage of light into different parts of the photosite array such that certain locations on the photosite array only receive certain wavelengths of light reflected or fluoresced by the crop sample, wherein an electronics module is electrically connected to the photosite array and capable of determining which parts of the photosite array received light and the wavelengths of the light received, wherein the electronics module can analyze the optical data received by the photosite array, and wherein the analysis of the optical data is used to determine the composition of the crop sample.

Insect and other small object image recognition and instant response

A device for detecting offending objects such as insects on substrates such as on leaves, plants or in fluid. The device has a microscope lens which magnifies a portion of the substrate and sends an image of the substrate portion to an image recognition system. If the image recognition system detects the presence of an offending object—further steps are taken to remove, neutralize or mark the area where the offending object is located for subsequent action.

DATA PROCESSING SYSTEM AND DATA PROCESSING METHOD

A data processing system, a data processing device, and a data processing method are provided. The data processing system includes a wearable device including a display means and an imaging means and a database that is connected to the wearable device through a network. The database includes at least one of pieces of information on a cooking recipe, a cooking method, and a material. The wearable device detects a first material by the imaging means. The wearable device collects information on the first material from the database. When the first material exists in a specific region in an imaging range of the imaging means, the information on the first material is displayed on the display means. When the first material does not exist in the specific region, the information on the first material is not displayed on the display means. 1. A data processing system comprising:a wearable device including a display means and an imaging means anda database connected to the wearable device through a network,wherein the database includes at least one of pieces of information on a cooking recipe, a cooking method, and a material,wherein the wearable device detects a first material by the imaging means,wherein the wearable device collects information on the first material from the database,wherein when the first material exists in a specific region in an imaging range of the imaging means, the information on the first material is displayed on the display means, andwherein when the first material does not exist in the specific region, the information on the first material is not displayed on the display means.2. The data processing system according to claim 1 , wherein a cooking method using the first material is displayed on the display means based on the cooking recipe.3. The data processing system according to claim 1 , wherein the information on the first material contains a cutting position of the first material.4. The data processing system according to claim 1 , wherein the ...

In-oven camera and computer vision systems and methods

Systems and methods include a cooking appliance comprising a heating element disposed within a cooking chamber and operable to selectively emit waves at any of a plurality of powers and/or peak wavelengths, a camera operable to capture an image of the cooking chamber, and a computing device operable to supply power to the heating element to vary the power and/or peak wavelength of the emitted waves and generate heat within the cooking chamber, and instruct the camera to capture the image when the heating element is emitting at a stabilized power and/or peak wavelength. The computing device is operable to generate an adjusted captured image by adjusting the captured image with respect to the stabilized power and/or peak wavelength. The computing device comprises feedback components operable to receive the adjusted captured image, extract features, and analyze the one or more features to determine an event, property, measurement and/or status.

CURATED CONTEXTUAL OVERLAYS FOR AUGMENTED REALITY EXPERIENCES

Example systems, devices, media, and methods are described for curating and presenting a contextual overlay that includes graphical elements and virtual elements in an augmented reality experience. A contextual overlay application implements and controls the capturing of frames of video data within a field of view of the camera. The image processing system detects, in the captured frames of video data, one or more food items in the physical environment. Detecting food items may involve computer vision and machine-trained classification models. The method includes retrieving data associated with the detected food item, curating a contextual overlay based on the retrieved data and a configurable profile, and presenting the contextual overlay on the display. 1. A method of presenting a contextual overlay in response to items detected with an eyewear device in a physical environment , the eyewear device comprising a camera , a microphone , a loudspeaker , a contextual overlay application , an image processing system , and a display , the method comprising:perceiving a start command with the microphone;playing through the loudspeaker a confirming message in response to the perceived start command;capturing frames of video data within a field of view of the camera;with the image processing system, detecting in the captured frames of video data a food item at a current item position relative to the display;retrieving data associated with the detected food item with the contextual overlay application;curating a contextual overlay based on the retrieved data; andpresenting on the display the contextual overlay at an overlay position relative to the display.2. The method of claim 1 , further comprising:detecting a subsequent food item;retrieving subsequent data associated with the detected subsequent food item; andcurating further the contextual overlay based on the retrieved subsequent data.3. The method of claim 1 , wherein the process of retrieving data further comprises: ...

HARVESTING PLANTS BASED ON DETERMINED CRITERIA

A harvester travels along a route within a field and selectively harvests edible crowns ready for harvesting. As the harvester travels along the route, a position of the harvester and/or the edible crowns may be determined using an encoder, imaging device(s), and/or navigational system(s). For example, image(s) captured by the imaging device(s) may be used to determine a location of the edible crowns and/or global positioning satellite (GPS) coordinates may indicate a location of the harvester within the field. These locations may be used for instructing harvesting components to harvest the edible crowns. For example, the harvester may include robotic arms having end effectors that harvest the edible crowns. Knowing the location of the edible crowns and/or the harvester therefore allows for the accurate placement of the end effectors for harvesting the edible crowns.

SYSTEM AND METHODS TO OPTIMIZE YIELD IN INDOOR FARMING

A method for detecting stressed plants in an indoor farm includes the steps of receiving two consecutively taken images of a plantation area in the indoor farm captured consecutively at a predetermined interval. The two images are combined to form a composite image. To the composite image is applied an object detection network to segment the composite image into images of single plants. Pre-trained convolution neuronal networks can be applied to the images of single plants classifying the single plants as healthy or stressed. 1. A method for detecting stressed plants in an indoor farm , the method implemented by a processor and a memory , the method comprising the steps of:receiving two consecutively taken images of a plantation area from a camera captured at a predetermined interval;combining the two images to form a composite image;apply an object detection network to the composite image to segment the composite image into images of single plants; andapply a plurality of pre-trained convolution neuronal networks to the images of single plants to classify single plants in the images of single plants as healthy or stressed.2. The method according to claim 1 , wherein the predetermined interval ranges from minutes to days.3. The method according to claim 1 , wherein the method further comprises the steps of:determining a reason for the single plants getting stressed; andgenerate a notification with the reason.4. The method according to claim 3 , wherein the method further comprises the steps of:modifying one or more parameters of a nutrient management system and environment controller based on the reason.5. The method according to claim 1 , wherein the object detection network is configured to apply outlines around the single plants in the composite image claim 1 , wherein the composite image is segmented along the outlines.6. The method according to claim 1 , wherein the plurality of pre-trained convolution neuronal networks determines a plurality of predictions for ...

MACHINE LEARNING MODEL FOR ACCURATE CROP COUNT

A method comprising: receiving a set of images associated with each of a plurality of plants in a plantation; estimating, with respect to each of the plants, based, at least in part, on the set of images associated with the plant, the following data: (i) a count of fruits detected in the plant, and (ii) one or more features associated with the plant; at a training stage, training a machine learning model on a training set comprising, with respect to a subset of the plurality of plants: (iii) the data, and (iv) labels indicating an actual a number of fruits in each of the plants in the subset; and at an inference stage, applying the trained machine learning model to the data associated with the rest of the plurality of plants, to predict a number of fruits in each of the rest of the plurality of plants. 1. A system comprising:at least one hardware processor; and receive at least one image associated with each of a plurality of plants in a plantation,', 'estimating, with respect to each of said plurality of plants, based, at least in part, on said at least one image associated with said plant, data comprising:', '(i) a count of fruits detected in said plant, and', '(ii) one or more features associated with said plant,', 'at a training stage, training a machine learning model on a training set comprising, with respect to each plant in a selected subset of said plurality of plants:', '(iii) said data, and', '(iv) labels indicating an actual a number of fruits in each of said plants in said subset, and', 'at an inference stage, applying said trained machine learning model to said one or more images associated with one or more of said plurality of plants not included in said subset, to predict a number of fruits in said one or more plants., 'a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to2. The system of claim 1 , wherein said count of fruits ...

Monitoring grain quality

FIELD: agriculture. SUBSTANCE: invention relates to improvement of grain collection. Method of harvesting machine operation control includes gripping bulk-grain image carried by harvesting machine; using feature extractor to image to determine feature of bulk-grain in image; for each of a plurality of different locations of the sample in the image, a classification score is determined based on the bulk-grain feature at the sampling location for presentation of the material classification at the sampling location; outputting a signal indicative of quality of bulk-grain on images based on a set of classification points of different locations of the sample; automatic control of working settings of harvesting machine based on signal when harvesting machine field and when collecting bulk-grain by harvesting machine. Harvesting machine operation control method is implemented by a computer-readable medium with a cleaning machine program. EFFECT: proposed control method of harvesting machine operation and computer-readable medium containing program logic for control of harvesting machine operation, increases accuracy of selected grain collection. 19‬ cl, 18 dwg РОССИЙСКАЯ ФЕДЕРАЦИЯ (19) RU (11) (13) 2 720 867 C2 (51) МПК G06K 9/00 (2006.01) G06T 7/00 (2006.01) G06T 7/12 (2017.01) ФЕДЕРАЛЬНАЯ СЛУЖБА ПО ИНТЕЛЛЕКТУАЛЬНОЙ СОБСТВЕННОСТИ (12) ОПИСАНИЕ ИЗОБРЕТЕНИЯ К ПАТЕНТУ (52) СПК G06K 9/00 (2020.02); G06T 7/00 (2020.02); G06T 7/12 (2020.02) (21)(22) Заявка: 2015154467, 18.12.2015 (73) Патентообладатель(и): ДИР ЭНД КОМПАНИ (US), КАРНЕГИ МЕЛЛОН ЮНИВЕРСИТИ (US) 18.12.2015 Дата регистрации: 13.05.2020 Приоритет(ы): (30) Конвенционный приоритет: 26.12.2014 US 14/583,473 2 7 2 0 8 6 7 R U (56) Список документов, цитированных в отчете о поиске: MAJUMDAR S et al, "Classification of cereal grains using machine vision: iv. combined morphology, color, and texture models", AMERICAN SOCIETY OF AGRICULTURAL ENGINEERS., (20000101), vol. 43, no. 6, p. 1689 - 1694. MEGHA R SIDDAGANGAPPA et al, ...

Display control apparatus and recording medium

本発明の課題は、飲食物の外観を変更した画像を表示することで食事をコントロールすることが可能な表示制御装置および記録媒体を提供することにある。そのために、本発明の表示制御装置は、入力画像に飲食物の画像が含まれているか否かを検出する検出部と、前記検出部により飲食物の画像が検出されたとき、当該飲食物の外観を変更した画像を生成する画像生成部と、前記画像生成部により生成された画像を表示部に表示するよう制御する表示制御部と、を備える。 The subject of this invention is providing the display control apparatus and recording medium which can control a meal by displaying the image which changed the external appearance of food and drink. For this purpose, the display control device of the present invention detects when an image of food or drink is detected by the detection unit that detects whether or not an image of food or drink is included in the input image. An image generation unit that generates an image whose appearance has been changed, and a display control unit that controls to display the image generated by the image generation unit on the display unit.