The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 11, 2025

Filed:

Jun. 06, 2022
Applicants:

Denso Corporation, Kariya, JP;

Carnegie Mellon University, Pittsburgh, PA (US);

Inventors:

Prasanna Sivakumar, Pittsburgh, PA (US);

Shawn Hunt, Bethel Park, PA (US);

Kris Kitani, Pittsburgh, PA (US);

Matthew O'Toole, Pittsburgh, PA (US);

Yu-Jhe Li, Pittsburgh, PA (US);

Assignees:

DENSO CORPORATION, Kariya, JP;

Carnegie Mellon University, Pittsburgh, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01S 7/41 (2006.01); G01S 13/89 (2006.01); G01S 17/89 (2020.01); G06N 3/045 (2023.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
G01S 7/417 (2013.01); G01S 13/89 (2013.01); G01S 17/89 (2013.01); G06N 3/045 (2023.01); G06V 20/58 (2022.01);
Abstract

A method includes generating a radar-based intensity map and a lidar-based intensity map and performing one or more augmentation routines on the radar-based intensity map and the lidar-based intensity map to generate a radar input and a lidar input. The method includes generating a plurality of teacher-based bounding boxes and a plurality of student-based bounding boxes based on the radar input and the lidar input. The method includes determining a loss value of the plurality of student-based bounding boxes based on the plurality of teacher-based bounding boxes and a plurality of ground truth bounding boxes, updating one or more weights of the student neural network based on the loss value, and updating one or more weights of the teacher neural network based on a moving average associated with the one or more weights of the student neural network.


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