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:
Mar. 17, 2026

Filed:

Mar. 07, 2023
Applicant:

West Virginia University Board of Governors on Behalf of West Virginia University, Morgantown, WV (US);

Inventors:

Gianfranco Doretto, Morgantown, WV (US);

Matthew Richardson Keaton, Morgantown, WV (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/74 (2022.01); G06T 7/11 (2017.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06T 7/11 (2017.01); G06V 10/761 (2022.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

System and methods for object segmentation include providing a pre-trained neural network model to segment object instances based on a first set of images and a first loss function. The neural network, for a pixel, can generate a gradient flow that points towards a center of an object structure and provides a probability score indicating a probability of the pixel belonging to the object structure. An adapted neural network model can be generated from the pre-trained neural network model to account for domain shifted new input images by training the pre-trained neural network model on a second set of images and a loss function that comprises a contrastive flow loss component and a contrastive mask loss component.


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