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:
Nov. 04, 2025

Filed:

Jun. 05, 2023
Applicants:

Honda Motor Co., Ltd., Tokyo, JP;

The Board of Trustees of the Leland Stanford Junior University, Stanford, CA (US);

Inventors:

Enna Sachdeva, San Jose, CA (US);

Nakul Agarwal, San Francisco, CA (US);

Sean F. Roelofs, Soquel, CA (US);

Jiachen Li, Mountain View, CA (US);

Behzad Dariush, San Ramon, CA (US);

Chiho Choi, San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/58 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 20/58 (2022.01); G06V 10/7788 (2022.01); G06V 10/82 (2022.01);
Abstract

Systems and methods for training a neural network for generating a reasoning statement are provided. In one embodiment, a method includes receiving sensor data from a perspective of an ego agent. The method includes identifying a plurality of captured objects in the at least one roadway environment. The method includes receiving a set of ranking classifications for a captured object of the plurality of captured objects. The annotator reasoning statement is a natural language explanation for the applied attribute. The method includes generating a training dataset for the object type including the annotator reasoning statements of the set of ranking classifications that include the applied attribute from the plurality of importance attributes in the importance category. The method includes training the neural network to generate a generated reasoning statement based on the training dataset in response to a training agent detecting a detected object of the object type.


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