Invention Grant
- Patent Title: Machine learning based highway radar vehicle classification across multiple lanes and speeds
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Application No.: US16248525Application Date: 2019-01-15
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Publication No.: US11313950B2Publication Date: 2022-04-26
- Inventor: Ezekiel Kruglick , Michael Jaques , Seth Anderson , James Cikanek , Zachary Pearson , Randall Johnson , Aaron Becker , Levi Remily , Saad Bedros
- Applicant: Image Sensing Systems, Inc.
- Applicant Address: US MN St. Paul
- Assignee: Image Sensing Systems, Inc.
- Current Assignee: Image Sensing Systems, Inc.
- Current Assignee Address: US MN St. Paul
- Agency: Hertzberg, Turk & Associates, LLC
- Main IPC: G01S7/41
- IPC: G01S7/41 ; G06N3/08 ; G06V20/58

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.
Public/Granted literature
- US20200225321A1 MACHINE LEARNING BASED HIGHWAY RADAR VEHICLE CLASSIFICATION ACROSS MULTIPLE LANES AND SPEEDS Public/Granted day:2020-07-16
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