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:
Oct. 15, 2024

Filed:

Sep. 27, 2019
Applicant:

Mcafee, Llc, Santa Clara, CA (US);

Inventors:

Sherin M. Mathews, Santa Clara, CA (US);

Shivangee Trivedi, Plano, TX (US);

Amanda House, Plano, TX (US);

Celeste R. Fralick, Plano, TX (US);

Steve Povolny, Hillsboro, OR (US);

Steve Grobman, Plano, TX (US);

Assignee:

MCAFEE, LLC, San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 21/44 (2011.01); G06F 16/41 (2019.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06N 5/045 (2023.01); G06V 10/764 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01);
U.S. Cl.
CPC ...
H04N 21/44008 (2013.01); G06F 16/41 (2019.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06V 10/764 (2022.01); G06V 10/7788 (2022.01); G06V 10/7796 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01); G06N 5/045 (2013.01);
Abstract

Methods, apparatus, systems and articles of manufacture to improve deepfake detection with explainability are disclosed. An example apparatus includes a deepfake classification model trainer to train a classification model based on a first portion of a dataset of media with known classification information, the classification model to output a classification for input media from a second portion of the dataset of media with known classification information; an explainability map generator to generate an explainability map based on the output of the classification model; a classification analyzer to compare the classification of the input media from the classification model with a known classification of the input media to determine if a misclassification occurred; and a model modifier to, when the misclassification occurred, modify the classification model based on the explainability map.


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