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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.

Patent No.:

US 12354330 B1

PDFFull Text
Date of Patent:
Jul. 08, 2025

Filed:

Dec. 10, 2018

Information processing method, information processing apparatus, and program for selecting images for machine learning for self driving

Applicant:

Panasonic Intellectual Property Corporation of America, Torrance, CA (US);

Inventors:

Takuya Yamaguchi, Osaka, JP;

Kazunobu Ishikawa, Osaka, JP;

Assignee:

PANASONIC INTELLECTUAL PROPERTY CORPORATION OF AMERICA, Torrance, CA (US);

Attorney:

Wenderoth, Lind & Ponack, L.L.P.

Primary Examiner:

Andrew J Jung

Assistant Examiner:

Su-Ting Chuang

Int. Cl.
CPC ...
G06V 20/56 (2022.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/25 (2023.01); G06F 18/28 (2023.01); G06N 5/048 (2023.01); G06N 20/00 (2019.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01); H04L 67/12 (2022.01);
U.S. Cl.
CPC ...
G06V 10/772 (2022.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/251 (2023.01); G06F 18/28 (2023.01); G06N 5/048 (2013.01); G06N 20/00 (2019.01); G06V 10/774 (2022.01); G06V 20/56 (2022.01); H04L 67/12 (2013.01);
Abstract

Provided are an information processing method, an information processing apparatus, and a program that can increase a diversity of learning data for configurations or techniques of unspecified devices. The information processing method includes: obtaining sensor data obtained by a sensor installed in a vehicle, and at least one type of traveling data of the vehicle; associating the sensor data and the at least one type of traveling data with each other; determining a degree of difference of the at least one type of traveling data from the at least one type of one or more traveling data associated with one or more sensor data; and selecting the sensor data as learning data according to the degree of difference.

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