Patents by Inventor Alex David HEMSATH

Alex David HEMSATH has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Cognitive neuro-linguistic behavior recognition system for multi-sensor data fusion
    Patent number: 11991194
    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.
    Type: Grant
    Filed: July 6, 2021
    Date of Patent: May 21, 2024
    Assignee: Intellective Ai, Inc.
    Inventors: 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
  • COGNITIVE NEURO-LINGUISTIC BEHAVIOR RECOGNITION SYSTEM FOR MULTI-SENSOR DATA FUSION
    Publication number: 20220006825
    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.
    Type: Application
    Filed: July 6, 2021
    Publication date: January 6, 2022
    Applicant: Intellective Ai, Inc.
    Inventors: 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
  • COGNITIVE INFORMATION SECURITY USING A BEHAVIORAL RECOGNITION SYSTEM
    Publication number: 20190230108
    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.
    Type: Application
    Filed: December 11, 2018
    Publication date: July 25, 2019
    Applicant: Omni AI, Inc.
    Inventors: 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
  • Cognitive information security using a behavioral recognition system
    Patent number: 10187415
    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.
    Type: Grant
    Filed: March 26, 2017
    Date of Patent: January 22, 2019
    Assignee: Omni AI, Inc.
    Inventors: 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
  • COGNITIVE INFORMATION SECURITY USING A BEHAVIORAL RECOGNITION SYSTEM
    Publication number: 20180046613
    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.
    Type: Application
    Filed: March 26, 2017
    Publication date: February 15, 2018
    Applicant: Omni AI, Inc.
    Inventors: 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
  • Cognitive neuro-linguistic behavior recognition system for multi-sensor data fusion
    Patent number: 9639521
    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.
    Type: Grant
    Filed: August 11, 2014
    Date of Patent: May 2, 2017
    Assignee: Omni AI, Inc.
    Inventors: 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
  • COGNITIVE NEURO-LINGUISTIC BEHAVIOR RECOGNITION SYSTEM FOR MULTI-SENSOR DATA FUSION
    Publication number: 20150046155
    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.
    Type: Application
    Filed: August 11, 2014
    Publication date: February 12, 2015
    Inventors: 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