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:
Jun. 15, 2021

Filed:

Jun. 04, 2019
Applicant:

Beijing Institute of Technology, Beijing, CN;

Inventors:

Qiang Huang, Beijing, CN;

Xiaopeng Chen, Beijing, CN;

Di Fan, Beijing, CN;

Hyunwoo Kim, Beijing, CN;

Xuechao Chen, Beijing, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/66 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/66 (2013.01); G06K 9/00281 (2013.01); G06K 9/00993 (2013.01);
Abstract

The application discloses a multi-task learning incorporating dependencies method for bionic eye's face attribute recognition, which is as follows: Determine the first face attribute and the second face attribute for attribute recognition of facial image. Obtain the first recognition task branch and the second recognition task branch. Establish the task dependency between the first recognition task branch and the second recognition task branch to obtain the first transformed face attribute fully connected layer related to the second face attribute. and the second transformed face attribute fully connected layer related to the first face attribute. Feed the first transformed face attribute fully connected layer into the prediction layer to predict the first face attribute of facial image. And feed the second transformed face attribute fully connected layer into the prediction layer to predict the second face attribute of facial image. The multi-task learning incorporating dependencies method for bionic eye's face attribute recognition will be obtained according to the above steps.


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