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:
Dec. 29, 2020

Filed:

Nov. 19, 2018
Applicant:

Ppip Llc, Tempe, AZ (US);

Inventors:

Michael Fong, Chandler, AZ (US);

Neric Hsin-wu Fong, Tempe, AZ (US);

Stephen Kuo-Tung Seay Chan, Annapolis, MD (US);

Krishna Teja Tokola, Tempe, AZ (US);

Huyen Nguyen Ngoc Cam Le, Tempe, AZ (US);

Assignee:

PPIP, LLC, Tempe, AZ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06F 21/32 (2013.01); G06N 3/08 (2006.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01); H04L 29/06 (2006.01); G06N 20/00 (2019.01); H04W 12/06 (2009.01);
U.S. Cl.
CPC ...
G06F 21/32 (2013.01); G06K 9/00577 (2013.01); G06K 9/00892 (2013.01); G06K 9/46 (2013.01); G06K 9/6262 (2013.01); G06N 3/08 (2013.01); H04L 63/0861 (2013.01); G06K 9/00087 (2013.01); G06K 9/00979 (2013.01); G06N 20/00 (2019.01); H04W 12/06 (2013.01);
Abstract

In accordance with some embodiments, a training method for biometric identity and authentication is provided. The method includes obtaining biometric data from a plurality of sources. The method further includes extracting a plurality of feature vectors from the biometric data. The method also includes determining a plurality of identifiability scores correspondingly associated with the plurality of feature vectors, where each of the plurality of identifiability scores provides a quantitative characterization of a relative uniqueness of a corresponding one of the plurality of feature vectors. The method additional includes determining run-time authentication neural network parameters based on a function of the plurality of feature vectors, where the run-time authentication neural network parameters enable extraction of one or more feature vectors from biometric data of a particular user, and the run-time authentication neural network parameters are associated with the plurality of feature vectors determined to satisfy an error threshold.


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