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:
Jul. 17, 2018

Filed:

Sep. 08, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Somnath Asati, Chhatarpur, IN;

Soma Shekar Naganna, Bangalore, IN;

Abhishek Seth, Uttar Pradesh, IN;

Vishal Tomar, Meerut, IN;

Shashidhar R. Yellareddy, Bangalore, IN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/66 (2006.01); G06F 17/30 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/66 (2013.01); G06F 17/3028 (2013.01); G06F 17/30256 (2013.01); G06K 9/00221 (2013.01); G06K 9/6214 (2013.01); G06K 9/6248 (2013.01); G06K 9/6256 (2013.01);
Abstract

A system trains a facial recognition modeling system using an extremely large data set of facial images, by distributing a plurality of facial recognition models across a plurality of nodes within the facial recognition modeling system. The system optimizes a facial matching accuracy of the facial recognition modeling system by increasing a facial image set variance among the plurality of facial recognition models. The system selectively matches each facial image within the extremely large data set of facial images with at least one of the plurality of facial recognition models. The system reduces the time associated with training the facial recognition modeling system by load balancing the extremely large data set of facial images across the plurality of facial recognition models while improving the facial matching accuracy associated with each of the plurality of facial recognition models.


Find Patent Forward Citations

Loading…