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公开(公告)号：US11991194B2
公开(公告)日：2024-05-21
申请号：US17368586
申请日：2021-07-06
发明人： Ming-Jung Seow , Wesley Kenneth Cobb , Gang Xu , Tao Yang , Aaron Poffenberger , Lon W. Risinger , Kishor Adinath Saitwal , Michael S. Yantosca , David M. Solum , Alex David Hemsath , Dennis G. Urech , Duy Trong Nguyen , Charles Richard Morgan
IPC分类号： G06F40/00 , G06F40/226 , G06F40/242 , G06F40/289 , G06F40/30 , G06N20/00 , H04L9/40 , G06F40/247 , G06F40/253 , G06F40/284 , G06F40/40
CPC分类号： H04L63/1425 , G06F40/226 , G06F40/242 , G06F40/289 , G06F40/30 , G06N20/00 , H04L63/1408 , G06F40/247 , G06F40/253 , G06F40/284 , G06F40/40
摘要： Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.
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公开(公告)号：US10755131B2
公开(公告)日：2020-08-25
申请号：US16033264
申请日：2018-07-12
发明人： Wesley Kenneth Cobb , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal , Ming-Jung Seow , Gang Xu , Lon W. Risinger , Jeff Graham
摘要： Techniques are disclosed for extracting micro-features at a pixel-level based on characteristics of one or more images. Importantly, the extraction is unsupervised, i.e., performed independent of any training data that defines particular objects, allowing a behavior-recognition system to forgo a training phase and for object classification to proceed without being constrained by specific object definitions. A micro-feature extractor that does not require training data is adaptive and self-trains while performing the extraction. The extracted micro-features are represented as a micro-feature vector that may be input to a micro-classifier which groups objects into object type clusters based on the micro-feature vectors.
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公开(公告)号：US11914956B1
公开(公告)日：2024-02-27
申请号：US18088189
申请日：2022-12-23
发明人： Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
IPC分类号： G06F40/237 , G06F40/30
CPC分类号： G06F40/237 , G06F40/30
摘要： Techniques are disclosed for generating anomaly scores for a neuro-linguistic model of input data obtained from one or more sources. According to one embodiment, generating anomaly scores includes receiving a stream of symbols generated from an ordered stream of normalized vectors generated from input data received from one or more sensor devices during a first time period. Upon receiving the stream of symbols, generating a set of words based on an occurrence of groups of symbols from the stream of symbols, determining a number of previous occurrences of a first word of the set of words, determining a number of previous occurrences of words of a same length as the first word, and determining a first anomaly score based on the number of previous occurrences of the first word and the number of previous occurrences of words of the same length as the first word.
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公开(公告)号：US11727689B2
公开(公告)日：2023-08-15
申请号：US17378530
申请日：2021-07-16
发明人： Wesley Kenneth Cobb , Ming-Jung Seow , Gang Xu , Kishor Adinath Saitwal , Anthony Akins , Kerry Joseph , Dennis G. Urech
IPC分类号： H04N7/18 , G06V20/52 , G08B23/00 , G06N20/00 , G06V40/10 , G06F18/40 , G06V10/778 , H04N7/00 , G08B21/18 , G08B29/18 , G08B13/196
CPC分类号： G06V20/52 , G06F18/41 , G06N20/00 , G06V10/7788 , G06V20/53 , G06V40/103 , G08B21/182 , G08B23/00 , G08B29/185 , H04N7/002 , G08B13/19608
摘要： Alert directives and focused alert directives allow a user to provide feedback to a behavioral recognition system to always or never publish an alert for certain events. Such an approach bypasses the normal publication methods of the behavioral recognition system yet does not obstruct the system's learning procedures.
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公开(公告)号：US10855549B2
公开(公告)日：2020-12-01
申请号：US16568784
申请日：2019-09-12
发明人： Tao Yang , Ming-Jung Seow
摘要： Techniques are disclosed for processing data collected from network components for analysis by a machine learning engine of a Cognitive AI System. A network data processing driver receives a stream of data from a data collector which obtains data from one or more network data sources. The driver normalizes the stream of data to one or more feature values each corresponding to the network data sources and generates a sample vector from the feature values. The sample vector is formatted to be analyzed by the machine learning engine.
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公开(公告)号：US10853961B1
公开(公告)日：2020-12-01
申请号：US16130599
申请日：2018-09-13
IPC分类号： G06K9/62 , G06T7/60 , G06K9/00 , G06K9/20 , G06K9/46 , G06T7/00 , G06K9/52 , G06T7/90 , H04N5/33
摘要： Techniques are disclosed for generating a low-dimensional representation of an image. An image driver receives an image captured by a camera. The image includes features based on pixel values in the image, and each feature describes the image in one or more image regions. The image driver generates, for each of the plurality of features, a feature vector that includes values for that feature corresponding to at least one of the image regions. Each value indicates a degree that the feature is present in the image region. The image driver generates a sample vector from each of the feature vectors. The sample vector includes each of the values included in the generated feature vectors.
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公开(公告)号：US12094212B2
公开(公告)日：2024-09-17
申请号：US18213516
申请日：2023-06-23
发明人： Wesley Kenneth Cobb , Ming-Jung Seow , Gang Xu , Kishor Adinath Saitwal , Anthony Akins , Kerry Joseph , Dennis G. Urech
IPC分类号： H04N7/18 , G06F18/40 , G06N20/00 , G06V10/778 , G06V20/52 , G06V40/10 , G08B21/18 , G08B23/00 , G08B29/18 , H04N7/00 , G08B13/196
CPC分类号： G06V20/52 , G06F18/41 , G06N20/00 , G06V10/7788 , G06V20/53 , G06V40/103 , G08B21/182 , G08B23/00 , G08B29/185 , H04N7/002 , G08B13/19608
摘要： Alert directives and focused alert directives allow a user to provide feedback to a behavioral recognition system to always or never publish an alert for certain events. Such an approach bypasses the normal publication methods of the behavioral recognition system yet does not obstruct the system's learning procedures.
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公开(公告)号：US11586874B2
公开(公告)日：2023-02-21
申请号：US16860313
申请日：2020-04-28
发明人： Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
IPC分类号： G06N3/02
摘要： Techniques are disclosed for generating an anomaly score for a neuro-linguistic model of input data obtained from one or more sources. According to one embodiment, generating an anomaly score comprises receiving a score indicating how often a characteristic is observed in the input data. Upon receiving the score, comparing the score with an unusual score model to determine an unusualness score and comparing the unusualness score with an anomaly score model based on one or more unusual score models to generate the anomaly score indicating an overall unusualness for the input data.
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公开(公告)号：US11537791B1
公开(公告)日：2022-12-27
申请号：US17164210
申请日：2021-02-01
发明人： Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
IPC分类号： G06F40/30 , G06F40/237 , G06N20/00
摘要： Techniques are disclosed for generating anomaly scores for a neuro-linguistic model of input data obtained from one or more sources. According to one embodiment, generating anomaly scores includes receiving a stream of symbols generated from an ordered stream of normalized vectors generated from input data received from one or more sensor devices during a first time period. Upon receiving the stream of symbols, generating a set of words based on an occurrence of groups of symbols from the stream of symbols, determining a number of previous occurrences of a first word of the set of words, determining a number of previous occurrences of words of a same length as the first word, and determining a first anomaly score based on the number of previous occurrences of the first word and the number of previous occurrences of words of the same length as the first word.
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公开(公告)号：US11468660B2
公开(公告)日：2022-10-11
申请号：US16931921
申请日：2020-07-17
发明人： Wesley Kenneth Cobb , Rajkiran K. Gottumukkal , Kishor Adinath Saitwal , Ming-Jung Seow , Gang Xu , Lon W. Risinger , Jeff Graham
摘要： Techniques are disclosed for extracting micro-features at a pixel-level based on characteristics of one or more images. Importantly, the extraction is unsupervised, i.e., performed independent of any training data that defines particularly objects, allowing a behavior-recognition system to forgo a training phase and for object classification to proceed without being constrained by specify object definitions. A micro-feature extractor that does not require training data is adaptive and self-trains while performing the extraction. The extracted micro-features are represented as a micro-feature vector that may be input to a micro-classifier which groups object into object type clusters based on the micro-feature vectors.
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