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:
Feb. 23, 2021

Filed:

Apr. 23, 2019
Applicant:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Inventors:

Hao Wang, Shenzhen, CN;

Zhifeng Li, Shenzhen, CN;

Xing Ji, Shenzhen, CN;

Fan Jia, Shenzhen, CN;

Yitong Wang, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06N 3/02 (2006.01); G06K 9/46 (2006.01); G06K 9/36 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00228 (2013.01); G06K 9/00 (2013.01); G06K 9/00288 (2013.01); G06K 9/36 (2013.01); G06K 9/46 (2013.01); G06K 9/62 (2013.01); G06K 9/6256 (2013.01); G06K 9/6262 (2013.01); G06K 9/6284 (2013.01); G06N 3/02 (2013.01);
Abstract

An object detection training method can include receiving a training sample set in a current iteration of an object detection training process over an object detection neural network. The training sample set can include first samples of a first class and second samples of a second class. A first center loss value of each of the first and second samples can be determined. The first center loss value can be a distance between an eigenvector of the respective sample and a center eigenvector of the first or second class which the respective sample belongs to. A second center loss value of the training sample set can be determined according to the first center loss values of the first and second samples. A first target loss value of the current iteration can be determined according to the second center loss value of the training sample set.


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