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. 17, 2024

Filed:

Jan. 25, 2021
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Oron Nir, Herzliya, IL;

Royi Ronen, Tel Aviv, IL;

Ohad Jassin, Tel Mond, IL;

Milan M. Gada, Redmond, WA (US);

Mor Geva Pipek, Giv'Atayim, IL;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/70 (2022.01); G06F 18/21 (2023.01); G06F 18/211 (2023.01); G06F 18/214 (2023.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 40/16 (2022.01);
U.S. Cl.
CPC ...
G06V 40/173 (2022.01); G06F 18/211 (2023.01); G06F 18/2148 (2023.01); G06F 18/217 (2023.01); G06V 10/70 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 40/175 (2022.01);
Abstract

Aspects of the technology described herein improve an object recognition system by specifying a type of picture that would improve the accuracy of the object recognition system if used to retrain the object recognition system. The technology described herein can take the form of an improvement model that improves an object recognition model by suggesting the types of training images that would improve the object recognition model's performance. For example, the improvement model could suggest that a picture of a person smiling be used to retrain the object recognition system. Once trained, the improvement model can be used to estimate a performance score for an image recognition model given the set characteristics of a set of training of images. The improvement model can then select a feature of an image, which if added to the training set, would cause a meaningful increase in the recognition system's performance.


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