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:
May. 19, 2026

Filed:

Dec. 29, 2023
Applicants:

Fujitsu Limited, Kawasaki, JP;

B. G. Negev Technologies and Applications Ltd., AT Ben-gurion University, Beer Sheva, IL;

Inventors:

Omer Hofman, Beer Sheva, IL;

Amit Giloni, Beer Sheva, IL;

Ikuya Morikawa, Kawasaki, JP;

Toshiya Shimizu, Kawasaki, JP;

Yuval Elovici, Beer Sheva, IL;

Asaf Shabtai, Beer Sheva, IL;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06V 10/25 (2022.01); G06V 10/44 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); H04N 5/74 (2006.01);
U.S. Cl.
CPC ...
G06V 10/764 (2022.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06V 10/25 (2022.01); G06V 10/44 (2022.01); G06V 10/761 (2022.01); H04N 5/74 (2013.01);
Abstract

An information processing apparatus extracts a projection area of an object from an input scene containing a projection of the object, specifies each of second areas that are included in the extracted projection area of the object and that are similar to a plurality of first areas representing a feature of each of labels in a feature space, outputs a first classification result based on each of the plurality of labels indicating a state in which a distribution of combinations of the specified second areas and the first areas that are associated with the second areas is closer than a predetermined threshold; and determines whether or not an adversarial patch is included in the object by comparing the first classification result with a second classification result that is a result of classification of the objects obtained by inputting the input scene to a predetermined object detection model.


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