Living body detection method and living body detection system

A living body detection method and a living body detection system are provided. A radio-frequency signal reflected by an experiment living body is received, and raw sampling data of the RF signal are obtained. A feature extraction process is performed to generate initial training features of sampling datasets, wherein the initial training features respectively correspond to feature generation rules. A classification prediction model is established according to a posture of the experiment living body and the initial training features, and correlation feature weightings respectively corresponding to the initial training features are obtained. Preferred features corresponding to at least one of the feature generation rules are selected from the initial training features according to the correlation feature weightings. Another classification prediction model configured for determining a posture of a detection living body is established according to the posture of the experiment living body ...

Wire winding structure with segmented winding slot

Manufacturing method of layered frozen beverage for providing users with visual feast and multi-level chewing taste and drinking flavor during drinking

The invention relates to a manufacturing method of layered frozen beverage, which includes a solid layer forming step and a liquid filling step. The solid layer forming step includes a filling stage. The filling stage includes a filling process and a cooling process. The filling process is to fill a frozen body into a container, and then perform the cooling process for cooling the frozen body until the surface is solidified and thus finishing a solid layer. The liquid filling step is to fill the liquid into the container and place it on the solid layer. The manufacturing method of layered frozen beverage of the invention employs the cooling process in the solid layer forming step for clear layering, wherein the solid layer is tightly attached to the container for clearly separating the liquid to be above the solid layer, so as to provide users with visual feast and multi-level chewing taste and drinking flavor during drinking.

Image identifying method and image identifying device

Anti-theft system for vehicle

Combined glasses structure, rimless glasses, half-rim glasses and full-rim glasses

The invention discloses a pair of combined glasses which comprise eyeglass components, two glasses legs, rim components and nose pad components, wherein the eyeglass components comprise two pieces of eyeglass and a transverse beam; the two glasses legs are respectively detachably connected with the eyeglass components; the rim components comprise upper rims and lower rims; the upper rims and the lower rims are respectively detachably arranged on the upper edges and the lower edges of the eyeglass components; the nose pad components are detachably connected with the transverse beam and are capable of limiting and fixing the upper rims and/or lower rims arranged on the upper edges, lower edges and upper and lower edges of the two pieces of eyeglass. When people move in different modes, the upper rims and the lower rims of the rim components can be detached and combined, so that requirements of people can be met; rimless, half-rim and full-rim functions can be achieved through one pair of ...

Image identifying method and image identifying device

The disclosure provides an image identifying method and an image identifying device. The method includes: retrieving a first computer tomographic (CT) image, wherein the first CT image includes a plurality of first pixels; retrieving a plurality of second pixels from the first pixels, and generating a second CT image based on the second pixels; performing a contrast enhancement algorithm on the second CT image to adjust a contrast of the second CT image; identifying a first image region in the second CT image to generate a third CT image, wherein the first image region includes a first object; dividing the third CT image into a plurality of sub-images, and only reserving a specific image area corresponding to the first object in each sub-image; combining the sub-images into a fourth CT image; identifying an object type of the first object based on the fourth CT image.

Improved PET bottle

Connection alarm system

Method of manufacturing frozen product with rich taste

A method of manufacturing a frozen product with rich taste comprises an outer body ingredient injecting step and an outer body forming step. First, the outer body ingredient injecting step is injecting outer body ingredient into a mold. Then the outer body forming step is taking the outer body ingredient in the middle portion of the mold out. A first ingredient filling step is to fill first ingredient into the outer body, and a second ingredient filling step is to fill second ingredient into the outer body. All steps above are at specific time to make the frozen product with rich taste.

IMAGE IDENTIFYING METHOD AND IMAGE IDENTIFYING DEVICE

The disclosure provides an image identifying method and an image identifying device. The method includes: retrieving a first computer tomographic (CT) image including a plurality of first pixels; retrieving a plurality of second pixels from the first pixels, and generating a second CT image based on the second pixels; performing a contrast enhancement algorithm on the second CT image to adjust a contrast of the second CT image; identifying a first image region in the second CT image to generate a third CT image, wherein the first image region includes a first object; dividing the third CT image into a plurality of sub-images, and only reserving a specific image region corresponding to the first object in each sub-image; combining the sub-images into a fourth CT image; and identifying an object type of the first object based on the fourth CT image.

Power switching apparatus

Layered frozen drink

Image identifying method and image identifying device

The disclosure provides an image identifying method and an image identifying device. The method includes: retrieving a first computer tomographic (CT) image including a plurality of first pixels; retrieving a plurality of second pixels from the first pixels, and generating a second CT image based on the second pixels; performing a contrast enhancement algorithm on the second CT image to adjust a contrast of the second CT image; identifying a first image region in the second CT image to generate a third CT image, wherein the first image region includes a first object; dividing the third CT image into a plurality of sub-images, and only reserving a specific image region corresponding to the first object in each sub-image; combining the sub-images into a fourth CT image; and identifying an object type of the first object based on the fourth CT image.

Temple and lens hinge mechanism and glasses with same

The invention discloses a temples and lens assembly hinge mechanism which comprises a first body and a second body. The first body is provided with a pivot slot and a first pivot is arranged in the pivot slot. The first end of the second body is pivoted to the first pivot, and the second end of the second body is pivoted to a pivoting end of each temple. A fastener is arranged on the side opposite to the second body, a pivoting point of the fastener is in pivoted connection with the first pivot, a compression spring is arranged between the first end of the fastener and the second body, and the second end of the fastener is provided with a fixing part for being fixed to the lens assembly. The invention further discloses a pair of glasses which comprises two temples and the lens assembly; the two temples are respectively connected with the lens assembly through the temple and lens assembly hinge mechanism in a detachable way. Through the compression springs, the lens assembly can be detached ...

Glasses elastic hinge structure and glasses containing the same

Baking jig

Vehicular alarming system

Water reservoir cleaning alarm system

Current equalizing-type power supply device

Concentration detection apparatus

Living body detection method and living body detection system

A living body detection method and a living body detection system are provided. A radio-frequency (RF) signal reflected by an experiment living body is received, and a plurality of raw sampling data of the RF signal are obtained. Feature extraction process is performed according to the raw sampling data to generate a plurality of initial training features of a plurality of sampling datasets, wherein the initial training features is respectively corresponding to a plurality of feature generation rules. A classification prediction model is established according to the posture of the experiment living body and the initial training features, and a plurality of correlation feature weightings respectively corresponding to the initial training features are obtained. A plurality of preferred features corresponding to at least one of the feature generation rules are selected from the initial training features according to the correlation feature weightings. Another classification prediction model ...

LIVING BODY DETECTION METHOD AND LIVING BODY DETECTION SYSTEM

A living body detection method and a living body detection system are provided. A radio-frequency signal reflected by an experiment living body is received, and raw sampling data of the RF signal are obtained. A feature extraction process is performed to generate initial training features of sampling datasets, wherein the initial training features respectively correspond to feature generation rules. A classification prediction model is established according to a posture of the experiment living body and the initial training features, and correlation feature weightings respectively corresponding to the initial training features are obtained. Preferred features corresponding to at least one of the feature generation rules are selected from the initial training features according to the correlation feature weightings. Another classification prediction model configured for determining a posture of a detection living body is established according to the posture of the experiment living body and the preferred features.

Light emitting diode (LED) driving device

Peanut food and preparation method thereof further ensure softness, hardness stability and particle completeness

Disclosed herein provides a method of preparing peanut food, comprising steps of immersing a peanut raw material into a phosphate aqueous solution to perform softening and carrying out sterilization after removing the phosphate aqueous solution for immersing, thereby obtaining peanut food. Blanching step consistently used in the industry can be omitted by utilizing preparation method of the disclosure. The method does not only assist process simplification, reduce filling deviation but also has better softness and hardness, shape-retention and color for peanut. Moreover, phosphate ingested by consumers can be significantly decreased to assist consumers' physical health.

Wireless backup communication expansion module has the significant advantages of multiple backup functions

The present invention provides a wireless backup communication expansion module, which includes at least two wireless communication processing units compliant with the M.2 specification, at least one interface unit compliant with the B key specification, at least two mobile communication units, a bridge interface, and a connection interface. The present invention uses the test method of specifying the packet transmission task, so that when any wireless communication processing unit cannot normally establish a mobile communication channel, or when any wireless communication processing unit is detected to be disconnected, the other wireless communication processing unit establishes a backup mobile communication channel to achieve a backup mechanism of the mobile communication channel. Furthermore, when the number of the mobile communication units is increased to multiple, the multiple mobile communication units are also backup units, so that the wireless backup communication expansion module ...

Power supply featuring dual input power sources

Blood vessel suture mechanism

Switching LED driver

Combination glasses structure, rimless glasses, half-rim glasses and full-frame glasses

Training data increment method, electronic apparatus and computer-readable medium

A training data increment method, an electronic apparatus and a computer-readable medium are provided. The training data increment method is adapted for the electronic apparatus and includes the following steps. A training data set is obtained, wherein the training data set includes a first image and a second image. An incremental image is generated based on the first image and the second image. A deep learning model is trained based on the incremental image.

Portable electronic device and wound-size measuring method using the same

A wound-size measuring method for use in a portable electronic device is provided. The method includes the following steps: obtaining an input image via a camera device of the portable electronic device; using a CNN (convolutional neural network) model to recognize the input image, and selecting a part of the input image with the highest probability of containing a wound as an output wound image; and calculating an actual height and an actual width of the output wound image according to a lens-focal-length parameter reported by an operating system running on the portable electronic device, a plurality of reference calibration parameters corresponding to a pitch angle of the portable electronic device, and a pixel-height ratio and a pixel-width ratio of the output wound image.

Image identifying method and image identifying device

Image identifying method and image identifying device

Image recognition device and image recognition method

An image recognition method includes the following steps. An original image with a first resolution is received, and the first resolution of the original image is reduced to generate a low-resolution image with a second resolution. The first resolution is higher than the second resolution. The position of a target object in the low-resolution image is identified using an object detection model to obtain the target object coordinates in the low-resolution image. A target object image is segmented from the original image according to the target object coordinates in the low-resolution image, and the target object image is input into the image classification model. The target object type that corresponds to the target object image is determined using the image classification model.

Fish identification device and fish identification method

A fish identification method is provided. The fish identification method includes capturing an image through a processor, wherein the image includes a fish image. The fish identification method includes identifying a plurality of feature points of the fish image through a coordinate detection model and obtaining a plurality of sets of feature-point coordinates. Each of the plurality of sets of feature-point coordinates corresponds to each of the plurality of feature points. The fish identification method further includes calculating a body length or an overall length of the fish image according to the plurality of sets of feature-point coordinates of the image.

Portable electronic device and wound-size measuring method using the same

A wound-size measuring method for use in a portable electronic device is provided. The method includes the following steps: obtaining an input image via a camera device of the portable electronic device; using a CNN (convolutional neural network) model to recognize the input image, and selecting a part of the input image with the highest probability of containing a wound as an output wound image; and calculating an actual height and an actual width of the output wound image according to a lens-focal-length parameter reported by an operating system running on the portable electronic device, a plurality of reference calibration parameters corresponding to a pitch angle of the portable electronic device, and a pixel-height ratio and a pixel-width ratio of the output wound image.

Object counting system and object counting method

An object counting system crops images into multiple split images. When a distance between at least one side of a bounding box being associated with a position of a first object in the first split image and at least one side of a bounding box being associated with a position of a second object in the second split image adjacent to the first split image is less than a tolerance value, the processor combines the adjacent first split image and the second split second split image into a merged image, so that the first object and the second object are merged into a merged object. A processor calculates a prediction number of objects based on the objects contained in these split images and the merged objects in the merged image. The object counting system automatically counts the number of bug eggs, to save manpower and provide an accurate count.

Object counting system and object counting method

An object counting system crops images into multiple split images. When a distance between at least one side of a bounding box being associated with a position of a first object in the first split image and at least one side of a bounding box being associated with a position of a second object in the second split image adjacent to the first split image is less than a tolerance value, the processor combines the adjacent first split image and the second split second split image into a merged image, so that the first object and the second object are merged into a merged object. A processor calculates a prediction number of objects based on the objects contained in these split images and the merged objects in the merged image. The object counting system automatically counts the number of bug eggs, to save manpower and provide an accurate count.

Object detection device and method

An object detection device is provided in the invention. The object detection device includes an image-extraction device and a processor. The image-extraction device extracts a plurality of images and a plurality of depth images in a specific space, wherein each image corresponds to one of the depth images. The processor may detect objects in each image using an object detection model to obtain object information. The processor may calculate the depth value of each object in each depth image. The processor may input the depth value of each object into an object status model to determine the object status of each object. The processor may determine whether to enter the specific space based on the object information and the object status of each object. Therefore, the object detection device provided in the invention will be able to determine a suitable time to enter the specific space.

Object detection device and method

An object detection device is provided in the invention. The object detection device includes an image-extraction device and a processor. The image-extraction device extracts a plurality of images and a plurality of depth images in a specific space, wherein each image corresponds to one of the depth images. The processor may detect objects in each image using an object detection model to obtain object information. The processor may calculate the depth value of each object in each depth image. The processor may input the depth value of each object into an object status model to determine the object status of each object. The processor may determine whether to enter the specific space based on the object information and the object status of each object. Therefore, the object detection device provided in the invention will be able to determine a suitable time to enter the specific space.

紙箱結構改良

Multi-functional LED emergency lamp

Image identifying method and image identifying device

The disclosure provides an image identifying method and an image identifying device. The method includes: retrieving a first computer tomographic (CT) image including a plurality of first pixels; retrieving a plurality of second pixels from the first pixels, and generating a second CT image based on the second pixels; performing a contrast enhancement algorithm on the second CT image to adjust a contrast of the second CT image; identifying a first image region in the second CT image to generate a third CT image, wherein the first image region includes a first object; dividing the third CT image into a plurality of sub-images, and only reserving a specific image region corresponding to the first object in each sub-image; combining the sub-images into a fourth CT image; and identifying an object type of the first object based on the fourth CT image.

Tire-size identification method, tire-size identification system and computer-readable storage medium

A tire-size identification method includes the following steps. An object-detection model frames a tire image in an image to generate a framed tire image. The framed tire image is input into an image-segmentation model. The image-segmentation model outputs the tire inner diameter of the tire. Moreover, the tire inner diameter is input into a classification model. The classification model outputs the tire size.

L型顯示溫度之奶瓶