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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 12061989 B1

PDFFull Text
Date of Patent:
Aug. 13, 2024

Filed:

Feb. 26, 2021

Machine learning artificial intelligence system for identifying vehicles

Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Sunil Subrahmanyam Vasisht, Flowermound, TX (US);

Geoffrey Dagley, McKinney, TX (US);

Qiaochu Tang, The Colony, TX (US);

Sean Reddy, New York, NY (US);

Jason Richard Hoover, Grapevine, TX (US);

Stephen Michael Wylie, Carrollton, TX (US);

Micah Price, Plano, TX (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:

FINNEGAN, HENDERSON, FARABOW, GARRETT & DUNNER LLP

Primary Examiner:

Brian Werner

Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06F 16/583 (2019.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06N 3/02 (2006.01); G06N 3/045 (2023.01); G06N 3/048 (2023.01); G06N 3/084 (2023.01); G06N 20/00 (2019.01); G06V 10/10 (2022.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 20/20 (2022.01); G06F 18/23 (2023.01); G06N 5/01 (2023.01); G06N 20/20 (2019.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06F 16/583 (2019.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06N 3/02 (2013.01); G06N 3/045 (2023.01); G06N 3/048 (2023.01); G06N 20/00 (2019.01); G06V 10/17 (2022.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 20/20 (2022.01); G06F 18/23 (2023.01); G06N 5/01 (2023.01); G06N 20/20 (2019.01); G06V 2201/10 (2022.01);
Abstract

An artificial intelligence system for identifying attributes in an image. The system may include a processor in communication with a client device; and a storage medium. The storage medium may store instructions that, when executed, configure the processor to perform operations including: extracting first features; categorizing the first images in a first group or a second group; modifying first metadata associated with each image in the first images to include a binary label; calculating a classification function; classifying a second plurality of images using the classification function; extracting second features from the second images classified in the first group; categorizing the second images in the first group by attribute; calculating an attribute identification function that identifies attributes of the second images; and identifying at least one attribute associated with a client image using the attribute identification function, the client image being received from the client device.

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