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:
Jul. 25, 2023

Filed:

Dec. 01, 2021
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Ankit Chadha, Palo Alto, CA (US);

Caiming Xiong, Palo Alto, CA (US);

Ran Xu, Mountain View, CA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06T 3/40 (2006.01); G06T 3/60 (2006.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06T 3/20 (2006.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 10/20 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/217 (2023.01); G06F 18/2148 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 3/20 (2013.01); G06T 3/40 (2013.01); G06T 3/60 (2013.01); G06V 10/20 (2022.01); G06V 10/764 (2022.01); G06V 10/809 (2022.01); G06V 10/82 (2022.01);
Abstract

Computing systems may support image classification and image detection services, and these services may utilize object detection/image classification machine learning models. The described techniques provide for normalization of confidence scores corresponding to manipulated target images and for non-max suppression within the range of confidence scores for manipulated images. In one example, the techniques provide for generating different scales of a test image, and the system performs normalization of confidence scores corresponding to each scaled image and non-max suppression per scaled image These techniques may be used to provide more accurate image detection (e.g., object detection and/or image classification) and may be used with models that are not trained on modified image sets. The model may be trained on a standard (e.g. non-manipulated) image set but used with manipulated target images and the described techniques to provide accurate object detection.


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