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:
Dec. 31, 2024

Filed:

Oct. 23, 2023
Applicant:

Nielsen Consumer Llc, Chicago, IL (US);

Inventors:

Roberto Arroyo, Guadalajara, ES;

David Jiménez-Cabello, Guadalajara, ES;

Javier Martínez Cebrián, Madrid, ES;

Assignee:

Nielsen Consumer LLC, Chicago, IL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/25 (2022.01); G06F 18/21 (2023.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06F 18/25 (2023.01); G06N 3/08 (2023.01); G06T 3/40 (2024.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/771 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01);
U.S. Cl.
CPC ...
G06V 10/25 (2022.01); G06F 18/2163 (2023.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06F 18/251 (2023.01); G06N 3/08 (2013.01); G06T 3/40 (2013.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/771 (2022.01); G06V 10/809 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01); G06V 2201/10 (2022.01);
Abstract

Example methods, apparatus, and articles of manufacture to classify labels based on images using artificial intelligence are disclosed. An example apparatus includes a regional proposal network to determine a first bounding box for a first region of interest in a first input image of a product; and determine a second bounding box for a second region of interest in a second input image of the product; a neural network to: generate a first classification for a first label in the first input image using the first bounding box; and generate a second classification for a second label in the second input image using the second bounding box; a comparator to determine that the first input image and the second input image correspond to a same product; and a report generator to link the first classification and the second classification to the product.


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