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:
Jan. 03, 2023

Filed:

Nov. 23, 2020
Applicant:

Nielsen Consumer Llc, New York, NY (US);

Inventors:

Emilio Almazan, Madrid, ES;

Aitor Aller Beascoechea, Madrid, ES;

Javier Tovar Velasco, Valladolid, ES;

Assignee:

Nielsen Consumer LLC, Chicago, IL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06V 10/22 (2022.01); G06V 10/26 (2022.01); G06V 10/426 (2022.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06Q 10/08 (2012.01);
U.S. Cl.
CPC ...
G06K 9/6262 (2013.01); G06K 9/6256 (2013.01); G06K 9/6277 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06V 10/23 (2022.01); G06V 10/267 (2022.01); G06V 10/426 (2022.01); G06Q 10/087 (2013.01);
Abstract

Methods, systems, articles of manufacture, and apparatus to recalibrate confidences for image classification are disclosed. An example apparatus to classify an image includes an image crop detector to detect a first image crop from the image, the first image crop corresponding to a first object, a grouping controller to select a second image crop corresponding to a second object at a location of the first object, a prediction generator to, in response to executing a trained model, determine a label corresponding to the first object and a confidence level associated with the label, and a confidence recalibrator to recalibrate the confidence level based on a probability of the first object having a first attribute based on the second object having a second attribute, the confidence level recalibrated to increase an accuracy of the image classification.


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