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:
Aug. 05, 2025

Filed:

Jun. 02, 2022
Applicant:

Vianai Systems, Inc., Palo Alto, CA (US);

Inventors:

Vishal Inder Sikka, Los Altos Hills, CA (US);

Kevin Frederick Dunnell, Waltham, MA (US);

Assignee:

VIANAI SYSTEMS, INC., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/764 (2022.01); G06N 3/08 (2023.01); G06V 10/72 (2022.01); G06V 10/74 (2022.01); G06V 10/75 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/764 (2022.01); G06N 3/08 (2013.01); G06V 10/72 (2022.01); G06V 10/74 (2022.01); G06V 10/751 (2022.01); G06V 10/761 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
Abstract

One embodiment of the present invention sets forth a technique for simplifying a trained machine learning model. The technique includes determining a first set of images associated with a first output class predicted by the trained machine learning model. The technique also includes generating a first aggregated representation of the first set of images, wherein the first aggregated representation includes a first plurality of representative pixel values for a plurality of pixel locations included in the first set of images. The technique further includes generating a simplified representation of the trained machine learning model that includes a first mapping of the first aggregated representation to the first output class, wherein the first mapping indicates that the trained machine learning model predicts the first output class for one or more input images.


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