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公开(公告)号：US10409910B2
公开(公告)日：2019-09-10
申请号：US14569161
申请日：2014-12-12
Applicant: Omni AI, Inc.
Inventor： Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
Abstract: Techniques are disclosed for generating a syntax for a neuro-linguistic model of input data obtained from one or more sources. A stream of words of a dictionary built from a sequence of symbols are received. The symbols are generated from an ordered stream of normalized vectors generated from input data. Statistics for combinations of words co-occurring in the stream are evaluated. The statistics includes a frequency upon which the combinations of words co-occur. A model of combinations of words based on the evaluated statistics is updated. The model identifies statistically relevant words. A connected graph is generated. Each node in the connected graph represents one of the words in the stream. Edges connecting the nodes represent a probabilistic relationship between words in the stream. Phrases are identified based on the connected graph.
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公开(公告)号：US10096235B2
公开(公告)日：2018-10-09
申请号：US13839587
申请日：2013-03-15
Applicant: Omni AI, Inc.
Inventor： Wesley Kenneth Cobb , Ming-Jung Seow , Gang Xu , Kishor Adinath Saitwal , Anthony Akins , Kerry Joseph , Dennis G. Urech
IPC: H04N7/18 , G08B29/18 , G08B23/00 , G06K9/00 , H04N7/00 , G06K9/32 , G06K9/62 , G06K9/52 , G08B21/18 , G08B13/196
Abstract: 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：US09973523B2
公开(公告)日：2018-05-15
申请号：US15363871
申请日：2016-11-29
Applicant: Omni AI, Inc.
Inventor： Wesley Kenneth Cobb , Ming-Jung Seow , Curtis Edward Cole, Jr. , Cody Shay Falcon , Benjamin A. Konosky , Charles Richard Morgan , Aaron Poffenberger , Thong Toan Nguyen
CPC classification number: H04L63/1425 , G06F17/2725 , G06F17/2735 , G06F17/274 , G06F17/277 , G06F17/2775 , G06F17/2785 , G06F17/2795 , G06F17/28 , G06N99/005 , H04L63/1408
Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.
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公开(公告)号：US10409909B2
公开(公告)日：2019-09-10
申请号：US14569104
申请日：2014-12-12
Applicant: Omni AI, Inc.
Inventor： Gang Xu , Ming-Jung Seow , Tao Yang , Wesley Kenneth Cobb
Abstract: Techniques are disclosed for building a dictionary of words from combinations of symbols generated based on input data. A neuro-linguistic behavior recognition system includes a neuro-linguistic module that generates a linguistic model that describes data input from a source (e.g., video data, SCADA data, etc.). To generate words for the linguistic model, a lexical analyzer component in the neuro-linguistic module receives a stream of symbols, each symbol generated based on an ordered stream of normalized vectors generated from input data. The lexical analyzer component determines words from combinations of the symbols based on a hierarchical learning model having one or more levels. Each level indicates a length of the words to be identified at that level. Statistics are evaluated for the words identified at each level. The lexical analyzer component identifies one or more of the words having statistical significance.
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公开(公告)号：US10187415B2
公开(公告)日：2019-01-22
申请号：US15469568
申请日：2017-03-26
Applicant: Omni AI, Inc.
Inventor： 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
Abstract: 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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Patent Agency Ranking
公开(公告)号：US10102642B2
公开(公告)日：2018-10-16
申请号：US14952090
申请日：2015-11-25
Applicant: Omni AI, Inc.
Inventor： Kishor Adinath Saitwal , Lon W. Risinger , Wesley Kenneth Cobb , Ming-Jung Seow , Gang Xu
Abstract: 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：US10373062B2
公开(公告)日：2019-08-06
申请号：US14569034
申请日：2014-12-12
Applicant: Omni AI, Inc.
Inventor： Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
Abstract: Techniques are disclosed for generating a sequence of symbols based on input data for a neuro-linguistic model. The model may be used by a behavior recognition system to analyze the input data. A mapper component of a neuro-linguistic module in the behavior recognition system receives one or more normalized vectors generated from the input data. The mapper component generates one or more clusters based on a statistical distribution of the normalized vectors. The mapper component evaluates statistics and identifies statistically relevant clusters. The mapper component assigns a distinct symbol to each of the identified clusters.
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公开(公告)号：US09639521B2
公开(公告)日：2017-05-02
申请号：US14457082
申请日：2014-08-11
Applicant: Omni AI, Inc.
Inventor： 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
CPC classification number: H04L63/1425 , G06F17/2725 , G06F17/2735 , G06F17/274 , G06F17/277 , G06F17/2775 , G06F17/2785 , G06F17/2795 , G06F17/28 , G06N99/005 , H04L63/1408
Abstract: 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：US10454777B2
公开(公告)日：2019-10-22
申请号：US15481320
申请日：2017-04-06
Applicant: OMNI AI, INC.
Inventor： Tao Yang , Ming-Jung Seow
Abstract: 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：US10423892B2
公开(公告)日：2019-09-24
申请号：US15090862
申请日：2016-04-05
Applicant: Omni AI, Inc.
Inventor： Gang Xu , Ming-Jung Seow , Tao Yang , Wesley Kenneth Cobb
IPC: G06K9/00 , G06N20/00 , G06K9/62 , G08B13/196 , G06K9/32
Abstract: Techniques are disclosed for analyzing and learning behavior in an acquired stream of video frames. In one embodiment, a trajectory analyzer clusters trajectories of objects depicted in video frames and builds a trajectory model including the trajectory clusters, a prior probability of assigning a trajectory to each cluster, and an intra-cluster probability distribution indicating the probability that a trajectory mapping to each cluster is least various distances away from the cluster. Given a new trajectory, a score indicating how unusual the trajectory is may be computed based on the product of the probability of the trajectory mapping to a particular cluster and the intra-cluster probability of the trajectory being a computed distance from the cluster. The distance used to match the trajectory to the cluster and determine intra-cluster probability is computed using a parallel Needleman-Wunsch algorithm, with cells in antidiagonals of a matrix and connected sub-matrices being computed in parallel.
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