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.
Patent No.:
Date of Patent:
Jul. 28, 2026
Filed:
Jul. 09, 2021
Applicant:
Wyze Labs, Inc., Kirkland, WA (US);
Inventors:
Assignee:
Wyze Labs, Inc., Kirkland, WA (US);
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/774 (2022.01); G06N 3/048 (2023.01); G06N 3/084 (2023.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06N 3/048 (2023.01); G06N 3/084 (2013.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 40/168 (2022.01); G06V 40/172 (2022.01);
Abstract
Introduced here is an approach to training a model to perform facial recognition with a designed dataset-aware loss. This approach is particularly useful for large-scale, multi-dataset training since there are no prerequisites for label cleaning. Dataset-aware loss may be built upon the softmax function with a binary dataset indicator. Such an approach allows the dataset-aware loss to be readily combined with other losses to improve performance.
Chen, Lin. (2026). Dataset-aware and invariant learning for face recognition (U.S. Patent No. 12694651). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12694651
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