Patents by Inventor Levi Remily

Levi Remily 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).

  • Machine learning based highway radar vehicle classification across multiple lanes and speeds
    Patent number: 11313950
    Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.
    Type: Grant
    Filed: January 15, 2019
    Date of Patent: April 26, 2022
    Assignee: Image Sensing Systems, Inc.
    Inventors: Ezekiel Kruglick, Michael Jaques, Seth Anderson, James Cikanek, Zachary Pearson, Randall Johnson, Aaron Becker, Levi Remily, Saad Bedros
  • MACHINE LEARNING BASED HIGHWAY RADAR VEHICLE CLASSIFICATION ACROSS MULTIPLE LANES AND SPEEDS
    Publication number: 20200225321
    Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.
    Type: Application
    Filed: January 15, 2019
    Publication date: July 16, 2020
    Applicant: Image Sensing Systems, Inc.
    Inventors: Ezekiel KRUGLICK, Michael Jaques, Seth Anderson, James Cikanek, Zachary Pearson, Randall Johnson, Aaron Becker, Levi Remily, Saad Bedros