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. 20, 2020

Filed:

Aug. 14, 2018
Applicant:

Kaikutek Inc., Taipei, TW;

Inventors:

Tsung-Ming Tai, New Taipei, TW;

Yun-Jie Jhang, Taoyuan, TW;

Wen-Jyi Hwang, Taipei, TW;

Chun-Hsuan Kuo, San Diego, CA (US);

Assignee:

KAIKUTEK INC., Taipei, TW;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G01S 13/89 (2006.01); G01S 7/41 (2006.01); G01S 13/58 (2006.01); G06T 7/20 (2017.01); G01S 13/50 (2006.01); G01S 7/35 (2006.01); G06K 9/00 (2006.01); G06K 9/20 (2006.01); G06K 9/46 (2006.01); G06N 20/00 (2019.01); G06F 3/01 (2006.01); G06F 9/50 (2006.01); G06N 3/08 (2006.01); H03B 21/02 (2006.01); G06F 17/18 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00335 (2013.01); G01S 7/414 (2013.01); G01S 7/417 (2013.01); G01S 13/584 (2013.01); G01S 13/89 (2013.01); G06F 3/017 (2013.01); G06F 9/5027 (2013.01); G06F 17/18 (2013.01); G06K 9/2018 (2013.01); G06K 9/4628 (2013.01); G06K 9/6215 (2013.01); G06K 9/6256 (2013.01); G06K 9/6259 (2013.01); G06K 9/6262 (2013.01); G06K 9/6267 (2013.01); G06K 9/6271 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06T 7/20 (2013.01); H03B 21/02 (2013.01); G01S 7/415 (2013.01); G01S 13/50 (2013.01); G01S 2007/356 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A performing device of a gesture recognition system for reducing a false alarm rate executes a performing procedure of a gesture recognition method for reducing the false alarm rate. The gesture recognition system includes two neural networks. A first recognition neural network is used to classify a gesture event, and a first noise neural network is used to determine whether the sensing signal is the noise. Since the first noise neural network can determine whether the sensing signal is the noise, the gesture event may not be executed when the sensing signal is the noise. Therefore, the false alarm rate may be reduced.


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