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:
May. 05, 2026

Filed:

Jan. 24, 2024
Applicants:

Kenvue Brands Llc, Summit, NJ (US);

Inria (Institut National DE Recherche En Informatique ET En Automatique), Les Chesnay-Cedex, FR;

Inventors:

Georgios N. Stamatas, Issy-les-Moulineaux, FR;

Imane Lboukili, Issy-les-Moulineaux, FR;

Xavier Descombes, Sophia Antipolis Cedex, FR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/60 (2024.01); G06T 5/20 (2006.01); G06T 5/70 (2024.01); G06T 7/00 (2017.01); G06T 7/60 (2017.01); G06T 7/73 (2017.01); G06T 11/00 (2006.01); G16H 30/40 (2018.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G06T 5/60 (2024.01); G06T 5/20 (2013.01); G06T 5/70 (2024.01); G06T 7/0016 (2013.01); G06T 7/60 (2013.01); G06T 7/73 (2017.01); G06T 11/00 (2013.01); G16H 30/40 (2018.01); G06T 2207/10056 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10101 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30088 (2013.01); G06V 10/774 (2022.01);
Abstract

Systems and methods for improving the image quality of images of epithelial tissue structures are disclosed. The systems include training a first cycle-GAN model and a second cycle-GAN model simultaneously, where the first cycle-GAN model is trained to remove noise from an image and the second cycle-GAN model is trained to learn the structure of the image. Additional systems and methods include deploying the trained cycle-GAN model to identify an unknown image segment and/or generate a protocol for following the identified skin care treatment recommendation for an identified image segment.


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