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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 12561617 B1

PDFFull Text
Date of Patent:
Feb. 24, 2026

Filed:

May. 13, 2022

Information processing apparatus, information processing method, and storage medium

Applicant:

Canon Kabushiki Kaisha, Tokyo, JP;

Inventor:

Atsushi Nogami, Kanagawa, JP;

Assignee:

Canon Kabushiki Kaisha, Tokyo, JP;

Attorney:

Venable LLP

Primary Examiner:

Quoc A Tran

Int. Cl.
CPC ...
G06N 20/20 (2019.01); A63B 71/06 (2006.01); B26D 5/00 (2006.01); B61G 5/04 (2006.01); G06F 18/20 (2023.01); G06F 18/21 (2023.01); G06N 3/045 (2023.01); G06N 3/0464 (2023.01); G06N 3/0475 (2023.01); G06T 7/00 (2017.01); G06V 10/70 (2022.01); G06V 10/75 (2022.01); G06V 10/778 (2022.01); G06V 10/94 (2022.01);
U.S. Cl.
CPC ...
G06N 20/20 (2019.01); G06V 10/75 (2022.01); G06V 10/7788 (2022.01); G06V 10/87 (2022.01); A63B 2071/0677 (2013.01); B26D 5/007 (2013.01); B60R 2300/30 (2013.01); B61G 5/04 (2013.01); G06F 18/2185 (2023.01); G06F 18/285 (2023.01); G06N 3/045 (2023.01); G06N 3/0464 (2023.01); G06N 3/0475 (2023.01); G06T 7/0004 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30132 (2013.01); G06T 2207/30184 (2013.01); G06V 10/945 (2022.01);
Abstract

An information processing apparatus comprising: a first acquiring unit configured to acquire information about learning data used in learning of each of a plurality of prelearned models for recognizing input data; a second acquiring unit configured to acquire information indicating an attribute of recognition target data; and a model selecting unit configured to select a model to be used in recognition of the recognition target data from the plurality of models, based on a degree of matching between the attribute of the recognition target data and an attribute of the learning data used in learning of each of the plurality of models, and on diversity of the attribute of the learning data used in learning of each of the plurality of models.

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