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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 16855. Отображено 100.
12-04-2012 дата публикации

Digital image analysis using multi-step analysis

Номер: US20120087556A1
Автор: Akira Nakamura, Jun Yokono, Shengyang Dai, Su Wang, Takeshi Ohashi
Принадлежит: Sony Corp

Systems and methods for implementing a multi-step image recognition framework for classifying digital images are provided. The provided multi-step image recognition framework utilizes a gradual approach to model training and image classification tasks requiring multi-dimensional ground truths. A first step of the multi-step image recognition framework differentiates a first image region from a remainder image region. Each subsequent step operates on a remainder image region from the previous step. The provided multi-step image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-step image recognition frameworks.

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Номер записи: 1
18-04-2013 дата публикации

Method for determining a preferred node in a classification and regression tree for use in a predictive analysis

Номер: US20130097109A1
Автор: Aspen L. Payton, James M. Caffrey, Karla K. Arndt
Принадлежит: International Business Machines Corp

Techniques are described for determining what node of a classification and regression tree (CART) should be used by a predictive analysis application. A first approach is to use a standard deviation of the data at a given the level of the CART to determine whether data in the next, lower node is more consistent than the data in the current node. A second approach is to measure a correlation between data points in a given node and the time at which each point was sampled (or other correlation metric) to identify a preferred node.

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Номер записи: 2
03-10-2013 дата публикации

System and method for root cause analysis of mobile network performance problems

Номер: US20130262656A1
Автор: Jin Cao, Li Erran Li, Susan Wu Sanders, Tian Bu
Принадлежит: Alcatel Lucent SAS

A method and system for identifying causes of performance metric changes in a network by selecting, from a pool of network event counters, a plurality of candidate counters relevant to a performance metric; grouping the candidate counters into clusters of similar counters; selecting, from each cluster, one or more representative counters; and fitting the selected representative counters to a model of the performance metric to determine thereby a set of representative counters most relevant to the performance metric.

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Номер записи: 3
07-01-2021 дата публикации

Classification method and system for high-throughput transparent articles

Номер: US20210003512A1
Автор: Christian Kläger, Dominik Eugster, Igor Sosman, Stefanie Julia Willmann
Принадлежит: SCHOTT Schweiz AG

A method for detecting and classifying defects in high-throughput transparent articles such as syringes, vials, cartridges, ampules, and bottles is provided. The method includes the steps of providing a stream of the articles; capturing a first digital image of each of the articles in the stream; inspecting the first digital image for objects; determining parameters of the objects; performing a first classification step to classify the objects into a first defect class and a second defect class; performing a second classification step to classify the objects into a plurality of defect types using at least two second classification models; comparing at least one object parameter of a classified object with a predetermined defect type dependent threshold; classifying the article as defective or non-defective based on the comparing step; and separating defective articles from non-defective articles.

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Номер записи: 4
11-01-2018 дата публикации

System of joint brain tumor and cortex reconstruction

Номер: US20180008187A1
Автор: Bi Song, Chen-Rui Chou, Ming-Chang Liu
Принадлежит: Sony Corp

System for performing fully automatic brain tumor and tumor-aware cortex reconstructions upon receiving multi-modal MRI data (T1, T1c, T2, T2-Flair). The system outputs imaging which delineates distinctions between tumors (including tumor edema, and tumor active core), from white matter and gray matter surfaces. In cases where existing MRI model data is insufficient then the model is trained on-the-fly for tumor segmentation and classification. A tumor-aware cortex segmentation that is adaptive to the presence of the tumor is performed using labels, from which the system reconstructs and visualizes both tumor and cortical surfaces for diagnostic and surgical guidance. The technology has been validated using a publicly-available challenge dataset.

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Номер записи: 5
18-01-2018 дата публикации

Unobtrusive emotion recognition system

Номер: US20180014739A1
Автор: Charalampos Tsirmpas, Georgios Eleftheriou, Panagiotis Fatouros
Принадлежит: Sentio Solutions Inc

One variation of a system for unobtrusively recognizing emotions of users includes: a galvanic skin response sensor; a heart rate sensor; a skin temperature sensor; a motion sensor; and a controller configured to sample a sequence of biosignal values of a user from the galvanic skin response sensor, the heart rate sensor, the skin temperature sensor, and the motion sensor, to implement statistical tests, self-organising maps, and clustering techniques to identify of significant changes in characteristics of the sequence of biosignal values, and to predict an emotional status of the user based on the significant changes in characteristics of the sequence of biosignal values.

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Номер записи: 6
03-02-2022 дата публикации

Method and device for training tree model

Номер: US20220036250A1
Автор: Guosai Wang, Kun Chen, Xiaoyu FAN, Xu He
Принадлежит: Huakong Tsingjiao Information Technology Beijing Co Ltd

A method and device for training a tree model based on a dataset are disclosed. The dataset comprises m pieces of sample data and m sample labels, each sample data comprises n features, the features and feature values in the dataset are ciphertexts, the method comprises: generating, for the dataset, candidate splits based on ciphertexts; partitioning, for each candidate split, the dataset into a left and right subset based on ciphertexts; calculating a partition coefficient of each candidate split based on the left and right subset obtained through partition for each candidate split; determining a feature in a target candidate split as an optimal feature, determining a threshold in the target candidate split as an optimal splitting value, the optimal feature and the optimal splitting value are ciphertexts; assigning the dataset to two child nodes of the current node based on the optimal feature and the optimal splitting value.

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Номер записи: 7
16-01-2020 дата публикации

Systems and methods for generating a two-dimensional planogram based on intermediate data structures

Номер: US20200019908A1
Автор: Ehsan Nazarian, Manisha Goswami, Murthy Narayana Kolluru, Paul Michael Tempest, Rajesh Veliyanallore
Принадлежит: Walmart Apollo LLC

A system for generating a two-dimensional planogram. The system generates, for a facility in a cluster of facilities, a planogram for sets of items using an intermediate file.

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Номер записи: 8
28-01-2021 дата публикации

Generating compressed representations of sorted arrays of identifiers

Номер: US20210027115A1
Автор: Kevin J. Arunski, Sashka T. Davis
Принадлежит: EMC IP Holding Co LLC

A method includes obtaining an array of sorted identifiers to be stored in a designated portion of a memory of a given computing system, determining a segment size for splitting elements of the array into a plurality of segments, splitting the array into the plurality of segments based at least in part on the determined segment size, and compressing the plurality of segments to create a plurality of compressed segments. The method also includes generating a balanced binary search tree comprising a plurality of nodes each identifying a range of elements of the array corresponding to a given one of the segments and comprising a pointer to a given compressed segment corresponding to the given segment. The method further includes maintaining the balanced binary search tree and the compressed segments in the designated portion of the memory, and processing queries to the array utilizing the balanced binary search tree.

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Номер записи: 9
01-02-2018 дата публикации

Hierarchical classifiers

Номер: US20180032917A1
Автор: Brandon Niemczyk, Josiah Dede Hagen
Принадлежит: Trend Micro Inc

Examples relate to providing hierarchical classifiers. In some examples, a superclass classifier of a hierarchy of classifiers is trained with a first type of prediction threshold, where the superclass classifier classifies data into one of a number of subclasses. At this stage, a subclass classifier is trained with a second type of prediction threshold, where the subclass classifier classifies the data into one of a number of classes. The first type of prediction threshold of the superclass classifier and the second type of prediction threshold of the subclass classifier are alternatively applied to classify data segments.

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Номер записи: 10
30-01-2020 дата публикации

Reliability determination of workload migration activities

Номер: US20200034211A1
Автор: Keerthi B. Kumar, Nitin Madhusudan Agrawal, Pramod Kumar P, Shubham Shashikant Patil
Принадлежит: VMware LLC

Techniques for determining reliability of a workload migration activity are disclosed. In one embodiment, sub-tasks associated with the workload migration activity may be determined. Further, statistical data associated with an execution of the sub-tasks corresponding to different instances of the workload migration activity may be retrieved. Furthermore, a reliability model may be trained through machine learning using the statistical data to determine reliability of the workload migration activity. Then, the reliability of a new workload migration activity may be determined using the trained reliability model.

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Номер записи: 11
24-02-2022 дата публикации

Method and apparatus of processing information, method and apparatus of recommending information, electronic device, and storage medium

Номер: US20220058222A1
Автор: Daxiang Dong, Dianhai Yu, Lin Ma, Mo CHENG, Wei Tang, Zhihua Wu
Принадлежит: Beijing Baidu Netcom Science And Technology Co Ltd

The present disclosure provides a method of processing information, an apparatus of processing information, a method of recommending information, an electronic device, and a storage medium. The method includes: obtaining a tree structure parameter of a tree structure, wherein the tree structure is configured to index an object set used for recommendation; obtaining a classifier parameter of a classifier, wherein the classifier is configured to sequentially predict, from a top layer of the tree structure to a bottom layer of the tree structure, a preference node set whose probability of being preferred by a user is ranked higher in each layer, and a preference node set of each layer subsequent to the top layer of the tree structure is determined based on a preference node set of a previous layer of the each layer; and constructing a recalling model based on the tree structure parameter and the classifier parameter.

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Номер записи: 12
06-02-2020 дата публикации

Machine learning data extraction algorithms

Номер: US20200042591A1
Автор: Everaldo Aguiar, Jesper Lind
Принадлежит: SAP SE

Embodiments of the present disclosure pertain to extracting data corresponding to particular data types using machine learning algorithms. In one embodiment, a method includes receiving an image in a backend system, sending the image to an optical character recognition (OCR) component, and in accordance therewith, receiving a plurality of characters recognized in the image. The character set is matched against known values to generate candidate character strings. The character set is processed by one or more machine learning algorithms to produce features. For each candidate character string, the features are then processed by a random forest model to determine a final character string.

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Номер записи: 13
03-03-2022 дата публикации

Computer vision transaction monitoring

Номер: US20220067568A1
Автор: Joshua Migdal, Shayan Hemmatiyan
Принадлежит: NCR Corp

A machine-learning algorithm is trained on images with a set of diverse items to produce as output feature vectors in a feature-vector space derived for the set. New item images for new items are passed to the algorithm and new feature vectors are projected into the vector space. A classifier for each new item is trained on the new feature vectors to determine whether the new item is new item or is not that new item. During a transaction, an item code scanned for an item and an item image are obtained. The item image is passed to the algorithm, a feature vector is obtained, a corresponding classifier for the item code is retrieved, the feature vector is passed to the classifier, and a determination is provided as to whether the item image and item code matches a specific item that should be associated with the item code.

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Номер записи: 14
14-02-2019 дата публикации

PU Classifier For Detection of Travel Mode Associated with Computing Devices

Номер: US20190050624A1
Автор: Lily Chai, Morgan Herlocker
Принадлежит: Mapbox Inc

Digital data corresponding to a trace by a device is received. The digital data includes location data and time data obtained over a period of time and representing movement of the device. A set of derived values for the plurality of metrics are calculated from the sets of values corresponding to the metrics, and the set of derived values are compared to a binary classification model to determine whether the received digital data represents movement of a first type. The binary classification model was trained using a first set of traces representing the first type of movement and a second set of traces. In response to determining that the digital data represents movement of the first type, the received digital data corresponding to the trace is labelled with the first type of movement.

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Номер записи: 15
25-02-2021 дата публикации

Method for predicting fluctuation of circuit path delay on basis of machine learning

Номер: US20210056468A1
Автор: Bingqian Xu, Jingjing Guo, Jun Yang, Mengxiao LI, Peng CAO
Принадлежит: SOUTHEAST UNIVERSITY

A method for predicting the fluctuation of circuit path delay on the basis of machine learning, comprising the following steps: S1: selecting suitable sample characteristics by means of analyzing the relationship between circuit characteristics and path delay; S2: generating a random path by means of enumerating values of randomized parameters, acquiring the maximum path delay by means of performing Monte Carlo simulation on the random path, selecting a reliable path by means of the 3σ standard, and using the sample characteristics and path delay of the reliable path as a sample set (D); S3: establishing a path delay prediction model, and adjusting parameters of the model; S4: verifying the precision and stability of the path delay prediction model; S5: obtaining the path delay. The method for predicting the fluctuation of circuit path delay on the basis of machine learning has the advantages of high precision and low running time, thereby having remarkable advantages in the accuracy and efficiency of timing analysis.

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Номер записи: 16
13-02-2020 дата публикации

Learning device and learning method

Номер: US20200050963A1
Автор: Ryosuke Kasahara, Takuya Tanaka
Принадлежит: Individual

A learning device is configured to perform learning of a decision tree. The learning device includes a branch score calculator, and a scaling unit. The branch score calculator is configured to calculate a branch score used for determining a branch condition for a node of the decision tree based on a cumulative sum of gradient information corresponding to each value of a feature amount of learning data. The scaling unit is configured to perform scaling on a value related to the cumulative sum used for calculating the branch score by the branch score calculator to fall within a numerical range with which the branch score is capable of being calculated.

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Номер записи: 17
17-03-2022 дата публикации

Applied data quality metrics for physiological measurements

Номер: US20220079530A1
Автор: Behnoosh TAVAKOLI, John Vincenzo Capodilupo, Mostafa Ghannad-Rezaie
Принадлежит: Whoop Inc

A model of data quality is derived for physiological monitoring with a wearable device by comparing data from the wearable device to concurrent data acquisition from a ground truth device such as a chest strap or electrocardiography (EKG) heart rate monitor. With this comparative data, a machine learning model or the like may be derived to prospectively evaluate data quality based on the data acquisition context, as determined, for example, by other sensor data and signals from the wearable device.

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Номер записи: 18
27-02-2020 дата публикации

Automated facial recognition detection

Номер: US20200065565A1
Автор: Cheng-Fang Lin, Chih-Hsiung Liu, Hao-Ting Shih, Norman Kung
Принадлежит: International Business Machines Corp

A method and system for improving an automated facial recognition software system is provided. The method includes automatically detecting a face of a user via an IOT device. An image of the face is retrieved and image portions are extracted from the image and represented as a vector. The user is classified via determined facial feature attributes with respect to a plurality of user type weights stored in a cache and an initial user type of the user is determined. The vector and data indicating the initial user type are transmitted to a server and a process for inferring with respect to the initial user type, the vector, and images in a specified database associated with the initial user type, a final user type of the user s performed. An identity of the user is determined based on the inferring and the identity is transmitted to the IOT device

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Номер записи: 19
17-03-2016 дата публикации

Method and apparatus for counting person

Номер: US20160078323A1
Автор: Ho-Yub Jung, TESHOME Mikiyas
Принадлежит: SAMSUNG ELECTRONICS CO LTD

A counting method and apparatus are provided. The method and/or apparatus includes generating a regression tree by inputting information about a moving object contained in a plurality of images, in response to a new image being input, inputting information about a moving object contained in the new input image to the regression tree, and determining the number of people contained in the new image based on a result value of the regression tree.

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Номер записи: 20
05-03-2020 дата публикации

Method and system for creating aesthetic design at scale

Номер: US20200074225A1
Автор: Karan BHAVSAR, Mithun B S, Pankaj Doke, Sanjay Kimbahune, Sujit SHINDE, Sylvan Lobo
Принадлежит: Tata Consultancy Services Ltd

The use of gestures are increasing frequently. Normally these gestures are disconnected with each other. Therefore, various methods have been used for creating the gestural language. The existing methods for creating gestural language is difficult to learn and lacks design aesthetics. A method and system for creating aesthetic design language using a plurality of gestures is provided. The system takes in to account of aesthetics of the generated form of gestures and the user's constraints of movement—degrees of freedom. The system is using a socio-techno system which aids the machine assisted creation of aesthetic language for gestural interactions. A grammar has also been defined for creating the gestural language based on the domain. In the final stage of the system, the grammar and the form symbols are chosen/selected/published to present the interaction language to the user.

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Номер записи: 21
18-03-2021 дата публикации

Method of training random forest model, electronic device and storage medium

Номер: US20210081847A1
Автор: Ge Jin, Jing Xiao, LIANG Xu
Принадлежит: Ping An Technology Shenzhen Co Ltd

A method of training a random forest model, an electronic device and a storage medium. The method of training the random forest model includes analyzing, by a system of controlling model training, whether model training conditions are met or not; if the model training conditions are met, determining whether reconstructive training needs to be carried out on the random forest model or not; if the reconstructive training needs to be carried out on the random forest model, carrying out the reconstructive training on the random forest model by using sample data; if the reconstructive training does not need to be carried out on the random forest model, carrying out corrective training on the random forest model by using the sample data.

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Номер записи: 22
19-06-2014 дата публикации

Method for automatic behavioral phenotyping

Номер: US20140167958A1
Автор: Aharon Weissbrod, Genadiy VASSERMAN, Tali KIMCHI
Принадлежит: Yeda Research and Development Co Ltd

A method of identifying and classifying social complex behaviors among a group of model organisms, comprising implanting at least one RFID transponder in each model organism in said group of model organisms; enclosing said group of model organisms in a monitored space divided into RFID monitored segments; RFID tracking a position of each model organism by reading said at least one RFID transponder in each model organism over a period of time; capturing a sequence of images of each model organism over said period of time; and calculating at least one spatiotemporal model of each model organism based on time synchronization of said RFID tracked position of said model organism with said sequence of images.

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Номер записи: 23
25-03-2021 дата публикации

Data Conversion/Symptom Scoring

Номер: US20210089965A1
Автор: Ankit Sharma, Chris Bates, Frank HESTER, Matthew STICKLAND
Принадлежит: Phoenix Partnership Leeds Ltd, TPP

A computer system for generating a quantitative value relating to a negative health outcome, the computer system comprising: a conversion module configured to receive multiple sets of data items associated with patients and each comprising a descriptor and the time at which that event impacted the patient. The conversion module generates a training data structure which comprises for each patient an array of selected features, each selected feature associated with a numerical value representing a score indicative of the relevance of that feature to the prediction of the negative health outcome, and a label indicating if the patient exhibits the negative health outcome; and a machine learning model which is trained using the training data structure so as to be operable to generate a quantitative value relating to a negative health outcome for a patient with at least some of the features.

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Номер записи: 24
25-03-2021 дата публикации

Interactive training of a machine learning model for tissue segmentation

Номер: US20210090251A1
Автор: Aditya SISTA, Ganesh Kumar MOHANUR RAGHUNATHAN, Kedar Sapre, Sumit Kumar Jha, Ubhay Kumar
Принадлежит: Applied Materials Inc

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.

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Номер записи: 25
29-03-2018 дата публикации

Image recognition method and image recognition apparatus

Номер: US20180089187A1
Автор: Hiroto Yoshii, Masakazu Matsugu
Принадлежит: Canon Inc

An image recognition apparatus is provided which comprises a first extracting means for extracting, from every registration image previously registered, a set of registration partial images of a predetermined size, and a second extracting means for extracting, from an input new image, a set of new partial images of a predetermined size. The apparatus further comprises a discriminating means for discriminating an attribute of the new partial image based on a rule formed by dividing the set of the registration partial images extracted by the first extracting means, and a collecting means for deriving a final recognition result of the new image by collecting discrimination results by the discriminating means at the time when the new partial images as elements of the set of the new partial images are input.

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Номер записи: 26
19-03-2020 дата публикации

Computer-readable recoding medium, learning method, prediction method, learning apparatus, and prediction apparatus

Номер: US20200090064A1
Автор: Hiroaki Iwashita
Принадлежит: Fujitsu Ltd

A non-transitory computer-readable recording medium has stored therein a program that causes a computer to execute a process including: generating, from pieces of training data each including explanatory variables and an objective variable, a hypothesis set in which a plurality of hypotheses meeting a specific condition, each of the plurality of hypotheses being a combination of the explanatory variables, each of the pieces of training data being classified into any of the plurality of hypotheses; and performing a machine learning process to calculate a weight of each of the plurality of hypotheses included in the hypothesis set on a basis of whether each of the plurality of hypotheses includes each of the pieces of training data.

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Номер записи: 27
28-03-2019 дата публикации

Algorithm-specific neural network architectures for automatic machine learning model selection

Номер: US20190095756A1
Автор: Nipun Agarwal, Sam Idicula, Sandeep Agrawal, Venkatanathan Varadarajan
Принадлежит: Oracle International Corp

Techniques are provided for selection of machine learning algorithms based on performance predictions by trained algorithm-specific regressors. In an embodiment, a computer derives meta-feature values from an inference dataset by, for each meta-feature, deriving a respective meta-feature value from the inference dataset. For each trainable algorithm and each regression meta-model that is respectively associated with the algorithm, a respective score is calculated by invoking the meta-model based on at least one of: a respective subset of meta-feature values, and/or hyperparameter values of a respective subset of hyperparameters of the algorithm. The algorithm(s) are selected based on the respective scores. Based on the inference dataset, the selected algorithm(s) may be invoked to obtain a result. In an embodiment, the trained regressors are distinctly configured artificial neural networks. In an embodiment, the trained regressors are contained within algorithm-specific ensembles. Techniques are also provided for optimal training of regressors and/or ensembles.

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Номер записи: 28
12-05-2022 дата публикации

Method and system with optimization of lens module assembly

Номер: US20220150404A1
Автор: Eun Young Choi, Hye geun Min, Sung Hoon Kim, Ye Rim CHOI, Yeon Bin SON
Принадлежит: Industry Academic Cooperation Foundation of Kyonggi University, Samsung Electro Mechanics Co Ltd

A lens module assembly optimization method includes: in preparing a lens module including assembled N lenses respectively formed in cavities: receiving characteristic information of at least N lenses respectively formed in N cavity groups each including a respective plurality of cavities; and processing information for selecting N cavities from the N cavity groups, based on the characteristic information. A past cavity selection result, a fitness function configured based on data of the assembled N lenses or data of the prepared lens module according to the past cavity selection result, and a genetic algorithm are received or stored. The processing of the information includes updating chromosome entity information based on the fitness function and output chromosome information crossed or mutated based on the genetic algorithm from input chromosome information corresponding to the past cavity selection result, and processing the information based on the chromosome entity information and the characteristic information.

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Номер записи: 29
04-04-2019 дата публикации

Image based object detection

Номер: US20190102646A1
Автор: Ali Farhadi, Joseph Redmon
Принадлежит: Xnor AI Inc

Systems and methods are disclosed for image-based object detection and classification. For example, methods may include accessing an image from an image sensor; applying a convolutional neural network to the image to obtain localization data to detect an object depicted in the image and to obtain classification data to classify the object, in which the convolutional neural network has been trained in part using training images with associated localization labels and classification labels and has been trained in part using training images with associated classification labels that lack localization labels; annotating the image based on the localization data and the classification data to obtain an annotated image; and storing, displaying, or transmitting the annotated image.

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Номер записи: 30
19-04-2018 дата публикации

Defect Review Sampling and Normalization Based on Defect and Design Attributes

Номер: US20180107903A1
Автор: Poh Boon YONG
Принадлежит: KLA Tencor Corp

A decision tree and normalized reclassification are used to classify defects. Defect review sampling and normalization can be used for accurate Pareto ranking and defect source analysis. A defect review system, such as a broadband plasma tool, and a controller can be used to bin defects using the decision tree based on defect attributes and design attributes. Class codes are assigned to at least some of the defects in each bin. Normalized reclassification assigns a class code to any unclassified defects in a bin. Additional decision trees can be used if any bin has more than one class code after normalized reclassification.

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Номер записи: 31
30-04-2015 дата публикации

Fast single-pass interest operator for text and object detection

Номер: US20150117780A1
Автор: Victor Erukhimov
Принадлежит: Itseez Inc

The invention provides a method of using machine vision to recognize text and symbols, and more particularly traffic signs.

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Номер записи: 32
09-06-2022 дата публикации

Adaptive robustness certification against adversarial examples

Номер: US20220180172A1
Автор: Ian Michael Molloy, Jiyong Jang, Kevin Eykholt, Shiqi Wang, Taesung Lee
Принадлежит: International Business Machines Corp

Adaptive verifiable training enables the creation of machine learning models robust with respect to multiple robustness criteria. In general, such training exploits inherent inter-class similarities within input data and enforces multiple robustness criteria based on this information. In particular, the approach exploits pairwise class similarity and improves the performance of a robust model by relaxing robustness constraints for similar classes and increasing robustness constraints for dissimilar classes. Between similar classes, looser robustness criteria (i.e., smaller ϵ) are enforced so as to minimize possible overlap when estimating the robustness region during verification. Between dissimilar classes, stricter robustness regions (i.e., larger ϵ) are enforced. If pairwise class relationships are not available initially, preferably they are generated by receiving a pre-trained classifier and then applying a clustering algorithm (e.g., agglomerative clustering) to generate them. Once pre-defined or computed pairwise relationships are available, several grouping methods are provided to create classifiers for multiple robustness criteria.

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Номер записи: 33
07-05-2015 дата публикации

Decision Tree Construction for Automatic Classification of Defects on Semiconductor Wafers

Номер: US20150125064A1
Автор: Chien-Huei (Adam) Chen, Chris Maher, John Raymond Jordan, III, Patrick Huet, Tai-Kam Ng
Принадлежит: KLA Tencor Corp

Methods and systems for decision tree construction for automatic classification of defects on semiconductor wafers are provided. One method includes creating a decision tree for classification of defects detected on a wafer by altering one or more floating trees in the decision tree. The one or more floating trees are sub-trees that are manipulated as individual units. In addition, the method includes classifying the defects detected on the wafer by applying the decision tree to the defects.

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Номер записи: 34
13-05-2021 дата публикации

Systems and methods for training and evaluating machine learning models using generalized vocabulary tokens for document processing

Номер: US20210141861A1
Автор: Sudhakar Kalluri
Принадлежит: Oracle International Corp

Techniques are described herein for training and evaluating machine learning (ML) models for document processing computing applications using generalized vocabulary tokens. In some embodiments, an ML system determines a set of tokens for non-textual content in a plurality of documents. The ML system generates a fixed-length vocabulary that includes the set of tokens for the non-textual content. The ML system further generates for each respective document in a training dataset of documents, a respective feature vector based at least in part on which tokens in the fixed-length vocabulary occur in the respective document. The ML system trains a ML model based at least in part on the respective feature vector for each respective document in the training dataset.

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Номер записи: 35
16-04-2020 дата публикации

Systems and methods for predicting real-time behavioral risks using everyday images

Номер: US20200117901A1
Автор: Francis McClernon, Jason Oliver, Lawrence Carin, Matthew Engelhard
Принадлежит: Duke University

A system includes a camera configured to generate image data and a computing device in electronic communication with the camera. The computing device includes at least one processor and is configured to receive, from the camera, one or more images representative of a location. The computing device is further configured to apply a trained classifier to the one or more images to classify the location into one of at least two risk categories, wherein the classification is based on a likelihood of a subject performing a target behavior based on presence of the subject in the location. The computing device is additionally configured to issue a risk alert responsive to the trained classifier classifying the location into a high-risk category.

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Номер записи: 36
25-04-2019 дата публикации

Image Recognition System

Номер: US20190122384A1
Автор: Jason Lee Ertle, Kevin L. Hofstee, Shane K. Luke
Принадлежит: Nike Inc

Systems and methods for predicting items within content and using improved, fine-grained image classification techniques to produce images used to identify consumer products in the real-world by allowing for the recognition of a product using an image captured under a variety of conditions and environments, such as angles, lighting, camera settings, and the like.

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Номер записи: 37
16-04-2020 дата публикации

Assigning privileges in an access control system

Номер: US20200120138A1
Автор: Chuan Yue, Matthew Westin Sanders
Принадлежит: COLORADO SCHOOL OF MINES

An access control system may include a log data parser that receives log data observations in a cloud system and extract user-permission data from the log data observations. The system may also include a clustering unit that uses the user-permission data to generate one or more clusters, each cluster associated with one or more users. Alternatively, and/or additionally, the system may include a feature extractor and a classifier. The feature extractor may extract one or more features from the user-permission data. The classifier may generate predictions of permissions for the one or more users based on the extracted one or more features. The system may also include a policy generator that uses the output of the clustering unit and/or the classifier to generate an access control policy. The policy may be executed in the cloud system to control user's access to one or more services of the system.

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Номер записи: 38
11-05-2017 дата публикации

Identification of item attributes using artificial intelligence

Номер: US20170132497A1
Автор: Adam James Finkelstein, Anthony Alexander Santos, David Akira Gingrich, David Michael Hurley, Siqi ZHAO
Принадлежит: Amazon Technologies Inc

A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.

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Номер записи: 39
07-08-2014 дата публикации

Methods, apparatuses and computer program products for efficiently recognizing faces of images associated with various illumination conditions

Номер: US20140219517A1
Автор: Krishna GovindaRao, Pranav MISHRA, Vinod PATHANGAY
Принадлежит: Nokia Oyj

An apparatus for recognizing faces with different illuminations may include a processor and memory storing executable computer program code causing the apparatus to at least perform operations including detecting and extracting face data of a first candidate face of a first image and a second candidate face of a second image. The first image is associated with a first light intensity and the second image associated with a second light intensity different from the first light intensity. The computer program code may further cause the apparatus to analyze face data to determine whether the first candidate face corresponds to an area in the first image that is substantially the same as an area of the second candidate face and evaluate data of the first and second areas to determine whether the first and second candidate faces are valid or invalid faces. Corresponding methods and computer program products are also provided.

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Номер записи: 40
02-05-2019 дата публикации

Telecommunications-Network Content Caching

Номер: US20190132414A1
Автор: Andrew Gapin, Elisa Hwei-Shan Yuen, Marie Grace Jacinto, Otto Fonseca Escudero, Paul Bongaarts
Принадлежит: T Mobile USA Inc

A telecommunication system can include a control device and a network gateway. The control device can determine cache-update instructions by operating trained computational models. The network gateway can receive cache-update instructions from the control device and transmit corresponding items of content to network terminals. In some examples, the network terminals can receive the items of content and store them in respective content caches at the at the network terminals. In some examples, the control device can determine respective content scores for at least two items of content; cluster the at least two items of content based at least in part on usage data associated with the network terminals to determine respective cluster labels for the at least two items of content; and determine the cache-update instructions based at least in part on the content scores, the cluster labels, and network-resource information.

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Номер записи: 41
10-06-2021 дата публикации

Training set sufficiency for image analysis

Номер: US20210174146A1
Автор: Milan M. Gada, Mor Geva PIPEK, Ohad Jassin, Oron NIR, Royi Ronen
Принадлежит: Microsoft Technology Licensing LLC

Aspects of the technology described herein improve an object recognition system by specifying a type of picture that would improve the accuracy of the object recognition system if used to retrain the object recognition system. The technology described herein can take the form of an improvement model that improves an object recognition model by suggesting the types of training images that would improve the object recognition model's performance For example, the improvement model could suggest that a picture of a person smiling be used to retrain the object recognition system. Once trained, the improvement model can be used to estimate a performance score for an image recognition model given the set characteristics of a set of training of images. The improvement model can then select a feature of an image, which if added to the training set, would cause a meaningful increase in the recognition system's performance

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Номер записи: 42
25-05-2017 дата публикации

Memory facilitation using directed acyclic graphs

Номер: US20170147947A1
Автор: Antonio Criminisi, Jamie Daniel Joseph Shotton, John Michael Winn, Pushmeet Kohli, Reinhard Sebastian Bernhard Nowozin, Toby Sharp
Принадлежит: Microsoft Technology Licensing LLC

Memory facilitation using directed acyclic graphs is described, for example, where a plurality of directed acyclic graphs are trained for gesture recognition from human skeletal data, or to estimate human body joint positions from depth images for gesture detection. In various examples directed acyclic graphs are grown during training using a training objective which takes into account both connection patterns between nodes and split function parameter values. For example, a layer of child nodes is grown and connected to a parent layer of nodes using an initialization strategy. In examples, various local search processes are used to find good combinations of connection patterns and split function parameters.

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Номер записи: 43
15-09-2022 дата публикации

Online monitoring method of nuclear power plant system based on isolation forest method and sliding window method

Номер: US20220291654A1
Автор: Longfei Shan, Xin AI, Xueying Huang, Yongkuo Liu
Принадлежит: Harbin Engineering University

The present disclosure relates to an online monitoring method of a nuclear power plant system based on an isolation forest method and a sliding window method. An isolation forest method used in the present disclosure is an abnormal detection model based on the idea of binary tree division, and has no requirements on the dimension and linear characteristics of monitoring data. In view of the characteristics of strong nonlinearity and high dimension of operation data of the nuclear power plant system, in the process of state monitoring, system abnormalities can be detected more quickly and accurately. In the present disclosure, a sliding window method is used to improve an isolation forest model, so that the improved isolation forest model has the functions of model online updating and real-time state monitoring, and the usability of an isolation forest state monitoring method is enhanced.

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Номер записи: 44
16-05-2019 дата публикации

Method of Using Machine Learning Algorithms in Analyzing Laboratory Test Results of Body Fluid to Detect Microbes in the Body Fluid

Номер: US20190147136A1
Автор: Chung-Chih Hung, Hsin-Yao Wang, Jang-Jih Lu, Yi-Ju Tseng
Принадлежит: Chang Gung Memorial Hospital, Chang Gung University CGU

A method of using machine learning algorithms in analyzing laboratory test results of body fluid to detect microbes in the body fluid includes using a body fluid detection module for analytic measurements in body fluid of a person to create biological samples; sending the biological samples of a plurality of persons and corresponding microbes infection statuses to perform machine learning algorithms to establish a microbes in body fluid prediction model; and sending data obtained from the body fluid detection of a patient for testing to the microbes in body fluid prediction model for operation and analysis in order to determine whether the microbes is present in body fluid.

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Номер записи: 45
16-05-2019 дата публикации

Searching method and system based on multi-round inputs, and terminal

Номер: US20190147345A1
Автор: Guang Lu, Qiang JU, Xiajun LUO
Принадлежит: Baidu Online Network Technology Beijing Co Ltd

A searching method and system based on multi-round inputs and a terminal are provided. The method comprises: acquiring search conditions input by a user in multiple searches; determining a multi-round property between at least two searches of the multiple searches; determining a search purpose of one of the search conditions, and determining that the search purpose of the one of the search conditions is a multi-round search purpose; generating search results based on the multi-round search purpose and search conditions input by the user; and ranking the generated search results, and determining and outputting an optimal search result. According to the searching method provided by the present application, a machine can understand a user's purpose under a continuous multi-round interactions by understanding the context, so that the use initiative of the user is improved.

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Номер записи: 46
16-05-2019 дата публикации

Estimation of human orientation in images using depth information

Номер: US20190147613A1
Автор: Fei Duan, Haibing Ren, Xiaobo Hu, Yimin Zhang
Принадлежит: Intel Corp

Techniques are provided for estimation of human orientation and facial pose, in images that include depth information. A methodology embodying the techniques includes detecting a human in an image generated by a depth camera and estimating an orientation category associated with the detected human. The estimation is based on application of a random forest classifier, with leaf node template matching, to the image. The orientation category defines a range of angular offsets relative to an angle corresponding to the human facing the depth camera. The method also includes performing a three dimensional (3D) facial pose estimation of the detected human, based on detected facial landmarks, in response to a determination that the estimated orientation category includes the angle corresponding to the human facing the depth camera.

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Номер записи: 47
07-06-2018 дата публикации

Target detection method and apparatus

Номер: US20180157938A1
Автор: Biao Wang, Changkyu Choi, Chao Zhang, Deheng QIAN, Hao Feng, Jae-Joon HAN, Jingtao XU
Принадлежит: SAMSUNG ELECTRONICS CO LTD

A method of detecting a target includes generating an image pyramid based on an image on which a detection is to be performed; classifying candidate areas in the image pyramid using a cascade neural network; and determining a target area corresponding to a target included in the image based on the plurality of candidate areas, wherein the cascade neural network includes a plurality of neural networks, and at least one neural network among the neural networks includes parallel sub-neural networks.

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Номер записи: 48
11-09-2014 дата публикации

Apparatus and method for tracking the position of each part of the body for golf swing analysis

Номер: US20140254883A1
Автор: An Jin Park, Jin Wook Kim, Sung Kuk Chun
Принадлежит: Korea Advanced Institute of Science and Technology KAIST

A position tracking apparatus includes: a depth image obtaining unit for obtaining a depth image; a database created by collecting depth images received from the depth image obtaining unit; a feature extracting unit for extracting features from each pixel of the depth image; a classifier training unit for training a classifier in order to determine the position of the parts of the body by receiving a feature set for each part of the body as inputs which are extracted by using the feature extracting unit from all of the depth images in the database; and a position determination unit for extracting features for each pixel of the depth image received by the depth image obtaining unit using the feature extracting unit in a state in which the classifier training unit trains the classifier, and for tracking the three-dimensional position of each part of the body through the classifier.

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Номер записи: 49
01-07-2021 дата публикации

System and method for determining service level metrics in bidding-based ridesharing

Номер: US20210199450A1
Автор: Bo Tan, Liang Tang
Принадлежит: Beijing Didi Infinity Technology and Development Co Ltd

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for bidding-based ridesharing are described. One exemplary method includes: obtaining a trip request for a rider, the trip request comprising a price; identifying a list of driver candidates to match with the trip request; determining a list of dispatch waiting times corresponding to the list of driver candidates; determining a list of acceptance probabilities corresponding to the list of driver candidates based on a machine-learning classifier; and determining an estimated waiting time or an estimated matching probability for the trip request based on the list of dispatch waiting times and the list of acceptance probabilities.

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Номер записи: 50
21-06-2018 дата публикации

Method and system for simultaneous scene parsing and model fusion for endoscopic and laparoscopic navigation

Номер: US20180174311A1
Автор: Ali Kamen, Stefan Kluckner, Terrence Chen
Принадлежит: SIEMENS AG

A method and system for scene parsing and model fusion in laparoscopic and endoscopic 2D/2.5D image data is disclosed. A current frame of an intra-operative image stream including a 2D image channel and a 2.5D depth channel is received. A 3D pre-operative model of a target organ segmented in pre-operative 3D medical image data is fused to the current frame of the intra-operative image stream. Semantic label information is propagated from the pre-operative 3D medical image data to each of a plurality of pixels in the current frame of the intra-operative image stream based on the fused pre-operative 3D model of the target organ, resulting in a rendered label map for the current frame of the intra-operative image stream. A semantic classifier is trained based on the rendered label map for the current frame of the intra-operative image stream.

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Номер записи: 51
06-06-2019 дата публикации

Method, system and apparatus for comparing objects in images

Номер: US20190171905A1
Автор: Getian Ye, Ka Ming Leung
Принадлежит: Canon Inc

A method of comparing objects in images. A dictionary determined from a plurality of feature vectors formed from a test image and codes formed by applying the dictionary to the feature vectors, is received. The dictionary is based on a modified manifold obtained by determining correspondences for codes using pairwise similarities between codes. Comparison codes are determined for the objects in the images by applying the dictionary to feature vectors of the objects in the images. The objects in the images are compared based on the comparison codes of the objects.

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Номер записи: 52
06-06-2019 дата публикации

Multiple Stage Image Based Object Detection and Recognition

Номер: US20190171912A1
Автор: Carlos Vallespi-Gonzalez, George Totolos, Jr., Joseph Lawrence Amato
Принадлежит: Uber Technologies Inc

Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.

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Номер записи: 53
22-06-2017 дата публикации

Conditional behavioural biometrics

Номер: US20170177999A1
Автор: Alesis NOVIK, Andrius SUTAS
Принадлежит: AIMBRAIN SOLUTIONS LTD

The present invention relates to an improved method of providing identification of a user or authentication of a user's identity. More particularly, the present invention relates to an improved method of providing identification of a user or authentication of a user's identity using conditional behavioural biometrics. The present invention seeks to provide an enhanced method of authenticating and/or identifying a user identity using conditional behavioural biometrics. According to a first aspect of the present invention, there is provided a method of generating a user profile for use in identifying and/or authenticating a user on a device, the device equipped with one or more sensors, the method comprising: generating a set of data points from sensory data collected by the one or more sensors; clustering the set of data points to produce a set of data clusters; developing a first classifier for the data clusters, the first classifier being operable to assign a further data point derived from a further user interaction with the computing device to one of the data clusters; and developing one or more further classifiers for at least one of the data clusters, the further classifier operable to identify and/or authenticate a user identity based on the further data point.

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Номер записи: 54
18-09-2014 дата публикации

Performing object detection operations via a graphics processing unit

Номер: US20140270551A1
Автор: Elif Albuz, Mateusz Jerzy BARANOWSKI, Shalini Gupta
Принадлежит: Nvidia Corp

In one embodiment of the present invention, a graphics processing unit (GPU) is configured to detect an object in an image using a random forest classifier that includes multiple, identically structured decision trees. Notably, the application of each of the decision trees is independent of the application of the other decision trees. In operation, the GPU partitions the image into subsets of pixels, and associates an execution thread with each of the pixels in the subset of pixels. The GPU then causes each of the execution threads to apply the random forest classifier to the associated pixel, thereby determining a likelihood that the pixel corresponds to the object. Advantageously, such a distributed approach to object detection more fully leverages the parallel architecture of the PPU than conventional approaches. In particular, the PPU performs object detection more efficiently using the random forest classifier than using a cascaded classifier.

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Номер записи: 55
08-07-2021 дата публикации

Detecting blocking objects

Номер: US20210208598A1
Автор: Benjamin John SAPP, Mahsa Ghafarianzadeh
Принадлежит: Zoox Inc

A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.

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Номер записи: 56
08-07-2021 дата публикации

Weapon detection and tracking

Номер: US20210209402A1
Автор: David E. Harrison, Jeremy C. Patton, John Dankovchik
Принадлежит: Algolook Inc

A method detects and tracks weapons. A frame of a video is received from a camera. A weapon in the frame detected using a weapon detection model. The weapon from the frame is classified using a weapon match classifier. A weapon alert is generated in response to classifying the weapon. The video is presented in response to the weapon alert.

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Номер записи: 57
04-06-2020 дата публикации

Method and system for elimination of fault conditions in a technical installation

Номер: US20200174462A1
Автор: Ajay Sirohi, Shamim Alam
Принадлежит: Individual

A method and system for eliminating a fault condition in a technical installation is provided. In one aspect, the method includes predicting an occurrence of the fault condition in at least a portion of the technical installation. The method also includes determining a root cause of the predicted fault condition. Additionally, the method includes identifying one or more mitigation actions to resolve the fault condition. Furthermore, the method includes determining an outcome associated with at least one of the one or more mitigation actions on the technical installation. The method also includes outputting on a device associated with a user at least one mitigation action to be implemented in the technical installation based on the determined impact.

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Номер записи: 58
15-07-2021 дата публикации

Estimation system, estimation method, and estimation program

Номер: US20210216901A1
Автор: Kozo Banno, Tomohiro Hoshino, Toshiya Takano
Принадлежит: Toshiba Corp, Toshiba Energy Systems and Solutions Corp

An estimation model system, an estimation method, and an estimation program that can obtain an accuracy information for an estimation value is provided. The estimation system includes a learner 3 that creates an estimation model by machine learning from a correspondence relationship between a first input data and a first output data, an estimator 8 that estimates an output value obtained by inputting a data-for-estimation to the estimation model created by the learner 3 as a second estimation value which is an output value corresponding to the data-for-estimation, a precision estimation information creator 5 that acquires an accuracy reference information of a first estimation value obtained by inputting the first input data to the estimation model and creates a precision estimation information T which is a correspondence relationship between the first estimation value and the accuracy reference information, and a precision estimator 9 that acquires the accuracy reference information for the second estimation value based on the second estimation value and the precision estimation information T and acquires an accuracy information which is an estimation precision of the second estimation value based on the accuracy reference information for the second estimation value.

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Номер записи: 59
18-09-2014 дата публикации

System and Method for Remote Activity Detection

Номер: US20140280208A1
Автор: Adam Stotz, Katie McConky, Richard Viens, Thomas Fusillo, Travis Galoppo
Принадлежит: GRIDGLO LLC

A system and method is disclosed for a remote activity detection process using an analysis of data streams of an entity such as an end user and/or a customer. In an embodiment, the detection process uses the data stream analysis to evaluate an entity's potential involvement in an activity based on individual measures for the entity such as comparison of the entity's data stream to the entity's peers, comparison of the entity's data stream to historical information for the entity, and/or comparison of the entity's data stream to data streams for a known second entity involved in the activity. The detection process may also use other information available which may impact the data points in a data stream, such as premises attributes associated with an entity, demographic attributes for the entity, financial attributes for the entity, and system alerts.

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Номер записи: 60
20-06-2019 дата публикации

Privacy-preserving evaluation of decision trees

Номер: US20190190714A1
Автор: Fariborz SALEHI, Marc Joye
Принадлежит: NXP BV

A method for performing a secure evaluation of a decision tree, including: receiving, by a processor of a server, an encrypted feature vector x=(x1, . . . , xn) from a client; choosing a random mask μ0; calculating m0 and sending m0 to the client, wherein m0=xi0(0)−t0(0)+μ0 and t0(0) is a threshold value in the first node in the first level of a decision tree ′; performing a comparison protocol on m0 and μ0, wherein the server produces a comparison bit b0 and the client produces a comparison bit b0′; choosing a random bit s0∈{0,1} and when s0=1 switching a left and right subtrees of ′; sending b0⊕s0 to the client; and for each level =1, 2, . . . , d−1 of the decision tree ′, where d is the number of levels in the decision tree ′, perform the following steps: receiving from the client y0 where k=0, 1, . . . , −1; performing a comparison protocol on and , wherein is a random mask and is based upon, x, , yk, and and the server produces a comparison bit and the client produces a comparison bit ; choosing a random bit ∈{0,1} and when =1 switching all left and right subtrees at level of ′; and sending ⊕ to the client.

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Номер записи: 61
21-07-2016 дата публикации

Methods and systems for automatic selection of preferred size classification and regression trees

Номер: US20160210561A1
Автор: Dan Steinberg, Nicholas Scott Cardell
Принадлежит: Health Care Productivity Inc

Methods and systems for automatically identifying and selecting preferred size classification and regression trees are disclosed. The invention is used to identify a specific decision tree or group of preferred size trees that are consistent across train and test samples in node-specific details that are often important to decision makers. Specifically, for a tree to be identified as preferred by this system, the train and test samples must both agree on key measures for every terminal node of the tree. In addition to this node-by-node criterion, an additional tree selection method may be imposed. Accordingly, the train and test samples rank order the nodes on a relevant measure in the same way. Both consistency criteria may be applied in a fuzzy manner in which agreement must be close but need not be exact.

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Номер записи: 62
27-06-2019 дата публикации

Multi-modal medical image processing

Номер: US20190197366A1
Автор: Peter Kecskemethy, Tobias Rijken
Принадлежит: KHEIRON MEDICAL TECHNOLOGIES LTD

Aspects and/or embodiments seek to provide a method for training an encoder and/or classifier based on multimodal data inputs in order to classify regions of interest in medical images based on a single modality of data input source.

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Номер записи: 63
19-07-2018 дата публикации

System and method for contextual driven intelligence

Номер: US20180204059A1
Автор: Abhijit BENDALE, Anthony S. LIOT, Bo Li, Hyun Jae Kang, Jihee KIM, Lu LUO, Pranav K. Mistry, Simon J. Gibbs, Stanislaw Antol, Won J. Jeon, Zhihan Ying
Принадлежит: SAMSUNG ELECTRONICS CO LTD

A method includes retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof. At least one model is identified from multiple models based on the contextual information and at least one object recognized in an image based on at least one model. At least one icon is displayed at the device. The at least one icon being associated with at least one of an application, a service, or a combination thereof providing additional information.

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Номер записи: 64
19-07-2018 дата публикации

Vision intelligence management for electronic devices

Номер: US20180204061A1
Автор: Abhijit BENDALE, Anthony S. LIOT, Bo Li, Hyun Jae Kang, Jihee KIM, Lu LUO, Pranav K. Mistry, Simon J. Gibbs, Stanislaw Antol, Won J. Jeon, Zhihan Ying
Принадлежит: SAMSUNG ELECTRONICS CO LTD

One embodiment provides a method comprising classifying one or more objects present in an input comprising visual data by executing a first set of models associated with a domain on the input. Each model corresponds to an object category. Each model is trained to generate a visual classifier result relating to a corresponding object category in the input with an associated confidence value indicative of accuracy of the visual classifier result. The method further comprises aggregating a first set of visual classifier results based on confidence value associated with each visual classifier result of each model of the first set of models. At least one other model is selectable for execution on the input based on the aggregated first set of visual classifier results for additional classification of the objects. One or more visual classifier results are returned to an application running on an electronic device for display.

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Номер записи: 65
25-06-2020 дата публикации

Method for Fault Diagnosis of an Aero-engine Rolling Bearing Based on Random Forest of Power Spectrum Entropy

Номер: US20200200648A1
Автор: Jibang LI, Shuo Zhang, Tao Sun, Ximing SUN
Принадлежит: Dalian University of Technology

The present invention belongs to the technical field of fault diagnosis of aero-engines, and provides a method for fault diagnosis of an aero-engine rolling bearing based on random forest of power spectrum entropy. Aiming at the above-mentioned defects existing in the prior art, a method for fault diagnosis of an aero-engine rolling bearing based on random forest is provided, wherein test measured data for an aero-engine rolling bearing provided by a research institute are used for establishing a training dataset and a test dataset first; and based on an idea of fault feature extraction, time domain statistical analysis and frequency domain analysis are conducted on original collection data by adopting wavelet analysis; thereby realizing effective fault diagnosis from the perspective of engineering application.

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Номер записи: 66
05-08-2021 дата публикации

Method and apparatus for predicting destination, electronic device and storage medium

Номер: US20210239486A1
Автор: Feng Bing, Kaikai JIA, Yan Zhang, Zhenduo LIANG, Zichao YUAN
Принадлежит: Beijing Baidu Netcom Science And Technology Co Ltd

The present disclosure discloses a method and apparatus for predicting a destination, an electronic device and a storage medium, and relates to the field of artificial intelligence technology. A specific implementation comprises: acquiring personalized data of a user and space-time scenario data of the user at a current moment; predicting, through a pre-trained prediction model, a target destination of the user at the current moment based on the personalized data, the space-time scenario data and an attribute feature of each pre-determined candidate destination; and recommending the target destination to the user. The embodiment of the present disclosure may effectively improve the accuracy of the destination prediction and is suitable for more general travel scenarios, and thus, the user experience may be improved.

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Номер записи: 67
25-06-2020 дата публикации

Systems, methods and devices for monitoring betting activities

Номер: US20200202134A1
Автор: Adrian BULZACKI, Muhammad Talal Ibrahim, Vlad CAZAN
Принадлежит: ARB Labs INC

A platform, device and process for capturing images of the surface of a gaming table and determining the quantity, identity, and arrangement of chips bet at a gaming table. Image data is captured corresponding to the one or more chips positioned in at least one betting area on a gaming surface of the respective gaming table and the data is processed to filter out the background, establish a two dimensional grid of points of interests and corresponding histograms for classifying the one or more chips through identifying a dominant classification of each row in the grid of points of interests.

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Номер записи: 68
05-08-2021 дата публикации

Multi-domain convolutional neural network

Номер: US20210243012A1
Автор: Ibrahima J. Ndiour, Omesh Tickoo, Shao-Wen Yang, Srenivas Varadarajan, Vallabhajosyula S. Somayazulu, Yen-Kuang Chen, Yiting Liao
Принадлежит: Intel Corp

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

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Номер записи: 69
23-10-2014 дата публикации

Systems and Methods for Pedestrian Detection in Images

Номер: US20140314271A1
Автор: Haibo LIU, Jian Zhang, Jingsong Xu, Philipp Zhang, Qiang Wu, Wei Chen, Zefeng Ni
Принадлежит: Huawei Technologies Co Ltd

System, apparatus, and method embodiments are provided for detecting the presence of a pedestrian in an image. In an embodiment, a method for determining whether a person is present in an image includes receiving a plurality of images, wherein each image comprises a plurality of pixels and determining a modified center symmetric local binary pattern (MS-LBP) for the plurality of pixels for each image, wherein the MS-LBP is calculated on a gradient magnitude map without using an interpolation process, and wherein a value for each pixel is a gradient magnitude.

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Номер записи: 70
20-08-2015 дата публикации

Learning method and apparatus for pattern recognition

Номер: US20150235109A1
Автор: Hiroto Yoshii, Masakazu Matsugu, Yusuke Mitarai
Принадлежит: Canon Inc

A method for information processing includes a learning process to generate a tree structured dictionary based on a plurality of patterns including a target object to be recognized. The method includes selecting a plurality of points from an input pattern based on a distribution of a probability that the target object to be recognized is present in the input pattern at each node of a tree structure generated in the learning process, and classifying the input pattern into a branch based on a value of a predetermined function that corresponds to values of the input pattern at selected plurality of points.

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Номер записи: 71
18-07-2019 дата публикации

Anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning

Номер: US20190221014A1
Автор: Hongzhi Wang
Принадлежит: International Business Machines Corp

Computationally efficient anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning is provided. In some embodiments, an input image is read. The input image has a first resolution. The input image is downsampled to a second resolution lower than the first resolution. The downsampled image is segmented into a plurality of labeled anatomical segments. Error correction is applied to the segmented image to generate an output image. The output image has the first resolution.

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Номер записи: 72
17-08-2017 дата публикации

Determining Depth from Structured Light Using Trained Classifiers

Номер: US20170236286A1
Автор: Adarsh Prakash Murthy Kowdle, Christoph RHEMANN, David Kim, Sean Ryan Francesco Fanello, Shahram Izadi, Vladimir Tankovich
Принадлежит: Microsoft Technology Licensing LLC

Techniques for determining depth for a visual content item using machine-learning classifiers include obtaining a visual content item of a reference light pattern projected onto an object, and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity for pixels based on the shifts in locations of the pixels relative to other pixels of a visual content item depicting in the reference light pattern. Disparity for pixels may be determined using a visual content item of a reference light pattern projected onto an object without having to match pixels between two visual content items, such as a reference light pattern and a captured visual content item.

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Номер записи: 73
16-07-2020 дата публикации

System, method, and computer-accessible medium for virtual pancreatography

Номер: US20200226748A1
Автор: Arie Kaufman, Konstantin DMITRIEV
Принадлежит: The Research Foundation for The State University of New York

A system, method, and computer-accessible medium for using medical imaging data to screen for a cystic lesion(s) can include, for example, receiving first imaging information for an organ(s) of a one patient(s), generating second imaging information by performing a segmentation operation on the first imaging information to identify a plurality of tissue types, including a tissue type(s) indicative of the cystic lesion(s), identifying the cystic lesion(s) in the second imaging information, and applying a first classifier and a second classifier to the cystic lesion(s) to classify the cystic lesion(s) into one or more of a plurality of cystic lesion types. The first classifier can be a Random Forest classifier and the second classifier can be a convolutional neural network classifier. The convolutional neural network can include at least 6 convolutional layers, where the at least 6 convolutional layers can include a max-pooling layer(s), a dropout layer(s), and fully-connected layer(s).

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Номер записи: 74
25-08-2016 дата публикации

Methods and systems for efficient automated symbol recognition using decision forests

Номер: US20160247019A1
Автор: Oleg Senkevich, Yury Georgievich Chulinin
Принадлежит: ABBYY Development LLC

The current document is directed to methods and systems for identifying symbols corresponding to symbol images in a scanned-document image or other text-containing image, with the symbols corresponding to Chinese or Japanese characters, to Korean morpho-syllabic blocks, or to symbols of other languages that use a large number of symbols for writing and printing. In one implementation, the methods and systems to which the current document is directed carry out an initial processing step on one or more scanned images to identify a set of graphemes that most likely correspond to each symbol image that occurs in the scanned document image. The graphemes are selected for a symbol image based on accumulated votes generated from symbol patterns identified as likely related to the symbol image using one or more decision forests.

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Номер записи: 75
23-07-2020 дата публикации

Automatic Malware Signature Generation for Threat Detection Systems

Номер: US20200233960A1
Автор: Benjamin ZELTSER, Dov Murik, Fady Copty, Matan DANOS, Orit Edelstein
Принадлежит: International Business Machines Corp

Deriving malware signatures by training a binary decision tree using known malware and benign software samples, each tree node representing a different software feature set and having one descending edge representing samples that are characterized by the node's software feature set and another descending edge representing samples that are not characterized thusly, selecting multiple continuous descending paths for multiple subsets of nodes, each path traversing a selected one of the edges descending from each of the nodes in its corresponding subset, deriving, based on the nodes and edges in any of the paths, a malware-associated software feature signature where the malware samples represented by leaves that directly or indirectly descend from an end of the continuous descending path meets a minimum percentage of the total number of samples represented by the leaves, and providing the malware signatures for use by a computer-based security tool configured to identify malware.

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Номер записи: 76
01-09-2016 дата публикации

Analyzing a parallel data stream using a sliding frequent pattern tree

Номер: US20160253366A1
Автор: Meichun Hsu, Qiming Chen
Принадлежит: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

A technique for analyzing a parallel data stream using a sliding FP tree can include create a sliding FP tree using input tuples belonging to a parallel sliding window boundary and analyze patterns of the parallel data stream in the parallel sliding window boundary.

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Номер записи: 77
08-09-2016 дата публикации

Learning method and recording medium

Номер: US20160260014A1
Автор: Reiko HAGAWA, Sotaro Tsukizawa, Yasunori Ishii
Принадлежит: Panasonic Intellectual Property Management Co Ltd

Learning method includes performing a first process in which a coarse class classifier configured with a first neural network is made to classify a plurality of images given as a set of images each attached with a label indicating a detailed class into a plurality of coarse classes including a plurality of detailed classes and is then made to learn a first feature that is a feature common in each of the coarse classes, and performing a second process in which a detailed class classifier, configured with a second neural network that is the same in terms of layers other than the final layer as but different in terms of the final layer from the first neural network made to perform the learning in the first process, is made to classify the set of images into detailed classes and learn a second feature of each detailed class.

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Номер записи: 78
30-07-2020 дата публикации

Target detection method and apparatus

Номер: US20200242424A1
Автор: Biao Wang, Changkyu Choi, Chao Zhang, Deheng QIAN, Hao Feng, Jae-Joon HAN, Jingtao XU
Принадлежит: SAMSUNG ELECTRONICS CO LTD

A method of detecting a target includes generating an image pyramid based on an image on which a detection is to be performed; classifying candidate areas in the image pyramid using a cascade neural network; and determining a target area corresponding to a target included in the image based on the plurality of candidate areas, wherein the cascade neural network includes a plurality of neural networks, and at least one neural network among the neural networks includes parallel sub-neural networks.

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Номер записи: 79
30-09-2021 дата публикации

Method and apparatus for optimizing video playback start, device and storage medium

Номер: US20210303938A1
Автор: Yuanfei GAO
Принадлежит: Beijing Baidu Netcom Science And Technology Co Ltd

A method and apparatus for optimizing a video playback start, a device and a storage medium are provided. An implementation of the method may include: acquiring feature data, the acquired feature data affecting the video playback start speed when a video starts to play; inputting the acquired feature data into a pre-trained gradient boosting decision tree (GBDT) regression model to output a predicted value for a video buffer frame, and recording the predicted value as a first predicted value; and ascertaining whether to start playing the video based on the first predicted value.

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Номер записи: 80
07-10-2021 дата публикации

Similarity learning-based device attribution

Номер: US20210312312A1
Автор: Nicholas Scott Eggert, Ramasubbu Venkatesh, Shalin S. Shah
Принадлежит: Target Brands Inc

Methods and systems for attributing browsing activity from two or more different network-connected devices to a single user are disclosed. In one aspect, cookies generated by the browsing activity of different unidentified devices at a website are received. A random forest classifier trained on probabilities output from a Gaussian mixture model is applied to the unidentified cookies to determine a probability that two different cookies were generated by the same user. In some embodiments, personalized content is then delivered to the user based on the characteristics of the paired cookies.

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Номер записи: 81
15-08-2019 дата публикации

Detecting blocking objects

Номер: US20190250626A1
Автор: Benjamin Sapp, Mahsa Ghafarianzadeh
Принадлежит: Zoox Inc

A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.

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Номер записи: 82
14-10-2021 дата публикации

Apparatus for determining a classifier for identifying objects in an image, an apparatus for identifying objects in an image and corresponding methods

Номер: US20210319269A1
Автор: Harald GALDA
Принадлежит: Leica Microsystems CMS GmbH

An apparatus for determining a classifier for identifying objects in an image is configured to receive a preliminary annotation for pixels of the image, the preliminary annotation comprising annotations for pixels to belong to an object or to background. The apparatus is further configured to transform the preliminary annotation to an enhanced annotation, the enhanced annotation further comprising at least one of annotations for pixels to belong to a transition between the background and an object, and annotations for pixel to belong to a transition between object. The classifier is determined based on the enhanced annotation and a representation of the pixels of the image.

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Номер записи: 83
21-09-2017 дата публикации

Computerized correspondence estimation using distinctively matched patches

Номер: US20170270390A1
Автор: Christoph RHEMANN, Pushmeet Kohli, Sean Ryan Francesco Fanello, Shahram Izadi, Shenlong Wang
Принадлежит: Microsoft Technology Licensing LLC

Correspondences in content items may be determined using a trained decision tree to detect distinctive matches between portions of content items. The techniques described include determining a first group of patches associated with a first content item and processing a first patch based at least partly on causing the first patch to move through a decision tree, and determining a second group of patches associated with a second content item and processing a second patch based at least partly on causing the second patch to move through the decision tree. The techniques described include determining that the first patch and the second patch are associated with a same leaf node of the decision tree and determining that the first patch and the second patch are corresponding patches based at least partly on determining that the first patch and the second patch are associated with the same leaf node.

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Номер записи: 84
04-11-2021 дата публикации

Methods for securing files within a storage device using artificial intelligence and devices thereof

Номер: US20210342674A1
Автор: Douglas Joseph Santry
Принадлежит: NetApp Inc

The present technology relates to identifying an artificial intelligence model based on a received first key value to write a received first block of data associated with a file. The received first key value is applied to the identified artificial intelligence model which is trained to output one of a plurality of actual index values where the identified artificial intelligence model and the plurality of data blocks are stored as a neural tree. The one of the actual index values is compared to a range within the actual index values to determine when the one of the actual index value points to a first data block of the plurality of data. The received first block of data associated with the file is written into the determined first data block.

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Номер записи: 85
20-08-2020 дата публикации

Semantic Place Recognition and Localization

Номер: US20200265232A1
Автор: Elmar Mair, Jonas Witt
Принадлежит: X Development LLC

Methods, systems, and apparatus for receiving data that represents a portion of a property that was obtained by a robot, identifying, based at least on the data, objects that the data indicates as being located within the portion of the property, determining, based on the objects, a semantic zone type corresponding to the portion of the property, accessing a mapping hierarchy for the property, wherein the mapping hierarchy for the property specifies semantic zones of the property that have corresponding semantic zone types and are associated with locations at the property, and specifies characteristics of the semantic zones, and selecting, from among the semantic zones and based at least on the semantic zone type and the data, a particular semantic zone, and setting, as a current location of the robot at the property, a particular location at the property associated with the particular semantic zone.

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Номер записи: 86
12-09-2019 дата публикации

Accumulate across stages in machine learning object detection

Номер: US20190279115A1
Автор: Edwin Chongwoo PARK
Принадлежит: Qualcomm Inc

Apparatus, methods, systems, and instructions stored on computer-readable medium are presented for performing classification. A hardware engine may be configurable to implement multiple stages of a cascade classifier including a first stage and a second stage. The hardware engine may be configurable to (a) access a value indicative of whether to accumulate, and (b) responsive to the value indicative of whether to accumulate meeting a continue evaluation condition, (i) access a first numeric value obtained from evaluation of the first stage of the cascade classifier, (ii) accumulate the first numeric value with a second numeric value obtained from evaluation of the second stage of the cascade classifier to generate an accumulated value, and (iii) utilize the accumulated value to determine an outcome for the second stage of the cascade classifier.

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Номер записи: 87
03-09-2020 дата публикации

Non-transitory computer-readable recording medium, determination method, and information processing apparatus

Номер: US20200279290A1
Автор: Keisuke Goto
Принадлежит: Fujitsu Ltd

A server inputs behavior information of a target to a trained machine learning model that learn a plurality of association relations obtained by associating combinations of behaviors generated from a plurality of behaviors included in a plurality of training data items with likelihoods indicating certainties that the combinations of the behaviors are in a specific state, the trained machine learning having been trained by using the plurality of training data items obtained by associating combinations of behaviors of persons corresponding to the specific state. The server specifies a difference between the combination of the behaviors in each of the plurality of association relations and the behavior information of the target based on output results of the trained machine learning model, and determines an additional behavior for causing the target to transit to the specific state based on the likelihood the difference.

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Номер записи: 88
19-09-2019 дата публикации

Automated intent to action mapping in augmented reality environments

Номер: US20190286906A1
Автор: John A. Bivens, Sinem Guven
Принадлежит: International Business Machines Corp

A method, computer system, and computer program product for mapping an intent to an action of a user in augmented reality procedures is provided. The present invention may include receiving a user activity from the user and monitoring the received user activity. The present invention may further include matching a concept with the monitored user activity, wherein the matched concept is extracted from an intent database. The present invention may further include identifying a task. The present invention may then include presenting a decision tree, from an intent database, wherein the decision tree comprises a plurality of intended steps to be performed by the user to complete a desired action. The present invention may also include, in response to determining that the user successfully performed an intended step within the plurality of intended steps, presenting a next intended step from the plurality of intended steps from the decision tree.

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Номер записи: 89
26-09-2019 дата публикации

Predictive use of quantitative imaging

Номер: US20190290210A1
Автор: Glen W. McLaughlin
Принадлежит: Shenzhen Mindray Bio Medical Electronics Co Ltd

The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

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Номер записи: 90
01-10-2020 дата публикации

Automatic weibull reliability prediction and classification

Номер: US20200311597A1
Автор: Bruce N. Edson, Robert McCarthy, Wilfredo E. Lugo Beauchamp
Принадлежит: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

A computing system and method for classifying a reliability distribution model for a part derived from empirical reliability data for the part includes a module for converting the reliability distribution model and the empirical reliability data into a plurality of data points in a matrix. The matrix is inputted to a machine-learned pattern recognition algorithm trained to assign the matrix to one of a predetermined plurality of classes. The machine-learned algorithm assigns the matrix to one of a predetermined plurality of classes according to an assessment, by the machine-learned pattern recognition algorithm, of the statistical fit between the reliability distribution model and the empirical reliability data on which the reliability distribution model was based.

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Номер записи: 91
17-10-2019 дата публикации

Two-class classification method for predicting class to which specific item belongs, and computing device using same

Номер: US20190318266A1
Автор: Chul Woo Kim, Kyung Nam Kang, Oh Ran Kwon, Yong Dai Kim
Принадлежит: Bioinfra Life Science Inc

A computing device of the present invention estimates an unknown parameter β of a model formula when distributed sample data is acquired, wherein when an estimated quantity of β is acquired, a function g is estimated using a random forest model, such that when an estimated quantity of g is acquired, the estimated quantity of g and the estimated quantity of β are used so as estimate a function G as a prediction formula for new data corresponding to a specific item such that an estimated quantity of G is acquired, and thus new data x new is received, thereby enabling the class of the specific item to be classified from the calculated value.

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Номер записи: 92
15-11-2018 дата публикации

Anomaly detection using non-target clustering

Номер: US20180330190A1
Автор: Georgios Ouzounis, Kostas Stamatiou
Принадлежит: DigitalGlobe Inc

A system and methods for radiometric anomaly detection using non-target clustering, wherein a hierarchy generator organizes the image information content into a hierarchical data representation structure, and a non-target clustering engine processes the hierarchical model to identify large homogeneous regions and significantly dissimilar smaller regions within them based on search criteria.

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Номер записи: 93
24-10-2019 дата публикации

Impression-tailored computer search result page visual structures

Номер: US20190325069A1
Автор: Abinash Sarangi, Aman Singhal, Hariharan RAGUNATHAN, Manish Mittal, Marcelo Medeiros De Barros, Prithvishankar Srinivasan, Rahul Lal, Saulo Santos
Принадлежит: Microsoft Technology Licensing LLC

A search engine query can be received, along with contextual data encoding information about a context of the query. The query can be classified into a selected user interface profile of multiple available user interface profiles, with the classifying including applying a classification model to the contextual data. A visual structure generator can be selected using results of the classifying, and a search results page can be generated for the query. The generating of the search results page can include using the selected visual structure generator to impose a selected visual structure on the search results page, with the selected visual structure corresponding to the selected visual structure generator. The generated search results page can be returned in response to the receiving of the query.

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Номер записи: 94
24-10-2019 дата публикации

Model interpretation

Номер: US20190325335A1
Автор: Mark Chan, Navdeep Gill, Patrick Hall
Принадлежит: H2oAi Inc

An indication of a selection of an entry associated with a machine learning model is received. One or more interpretation views associated with one or more machine learning models are dynamically updated based on the selected entry.

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Номер записи: 95
22-10-2020 дата публикации

Person tracking method, device, electronic device, and computer readable medium

Номер: US20200334466A1
Автор: Aixi ZHANG, Junhui Wu, Peiming ZHOU, YU Chen, Yun Ye, Zhi WENG
Принадлежит: Beijing Jingdong Century Trading Co Ltd, Beijing Jingdong Shangke Information Technology Co Ltd

A person tracking method, comprising: acquiring N frames in units of time windows; acquiring, in time windows, tracking paths of a target person according to the N frames; and constructing continuous tracking paths by means of continuous time windows, so as to obtain the tracking results of the target person.

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Номер записи: 96
06-12-2018 дата публикации

Multi Media Computing Or Entertainment System For Responding To User Presence And Activity

Номер: US20180348885A1
Автор: Chong Chen, FENG Tang, Haitao Guo, Thorsten Gernoth, Xiaojin Shi
Принадлежит: Apple Inc

Intelligent systems are disclosed that respond to user intent and desires based upon activity that may or may not be expressly directed at the intelligent system. In some embodiments, the intelligent system acquires a depth image of a scene surrounding the system. A scene geometry may be extracted from the depth image and elements of the scene may be monitored. In certain embodiments, user activity in the scene is monitored and analyzed to infer user desires or intent with respect to the system. The interpretation of the user's intent as well as the system's response may be affected by the scene geometry surrounding the user and/or the system. In some embodiments, techniques and systems are disclosed for interpreting express user communication, e.g., expressed through hand gesture movements. In some embodiments, such gesture movements may be interpreted based on real-time depth information obtained from, e.g., optical or non-optical type depth sensors.

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Номер записи: 97
14-11-2019 дата публикации

AI-Based Context Evaluation Engine Apparatuses, Methods and Systems

Номер: US20190347540A1
Автор: Brendan Hayes, Man Hei Raymond Yim, Yinchun Wang
Принадлежит: FMR LLC

The AI-Based Context Evaluation Engine Apparatuses, Methods and Systems (“ANDSE”) transforms embedding neural network training request, object search request, object evaluation request inputs via ANDSE components into embedding neural network response, object search response, object evaluation response outputs. Comparable context objects for a context object are determined. Relative values of the comparable context objects are calculated with regard to a benchmark object and used to calculate a relative value of the context object. The relative value is converted to a predicted price for the context object. Bid ask spreads for bid request objects are calculated. A spread win decision tree is constructed based on the calculated bid ask spreads and used to generate a spread win probability map for the context object. A spread is selected from the spread win probability map based on a desired winning bid confidence level and a bid price for the context object is calculated.

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Номер записи: 98
21-11-2019 дата публикации

Anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning

Номер: US20190355160A1
Автор: Hongzhi Wang
Принадлежит: International Business Machines Corp

Computationally efficient anatomy segmentation through low-resolution multi-atlas label fusion and corrective learning is provided. In some embodiments, an input image is read. The input image has a first resolution. The input image is downsampled to a second resolution lower than the first resolution. The downsampled image is segmented into a plurality of labeled anatomical segments. Error correction is applied to the segmented image to generate an output image. The output image has the first resolution.

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Номер записи: 99
20-12-2018 дата публикации

Machine learning and/or image processing for spectral object classification

Номер: US20180365535A1
Автор: Mark Gesley, Romin Puri
Принадлежит: Spynsite LLC

In one embodiment, a method of machine learning and/or image processing for spectral object classification is described. In another embodiment, a device is described for using spectral object classification. Other embodiments are likewise described.

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Номер записи: 100