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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.

Patent No.:

US 11650164 B1

PDFFull Text
Date of Patent:
May. 16, 2023

Filed:

Apr. 14, 2020

Artificial neural network-based method for selecting surface type of object

Applicant:

Getac Technology Corporation, Hsinchu County, TW;

Inventors:

Kun-Yu Tsai, Taipei, TW;

Po-Yu Yang, Taipei, TW;

Assignee:

GETAC TECHNOLOGY CORPORATION, Hsinchu County, TW;

Attorney:
Primary Examiner:

Kevin Ky

Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/40 (2017.01); G06V 20/64 (2022.01); G01N 21/88 (2006.01); G06T 7/586 (2017.01); G06N 3/08 (2023.01); G01N 21/3581 (2014.01); G06N 3/04 (2023.01); G06T 7/11 (2017.01); G01J 3/28 (2006.01); G01N 21/956 (2006.01); G06T 7/45 (2017.01); G06F 17/16 (2006.01); G06N 3/063 (2023.01); G01N 21/01 (2006.01); G01N 21/952 (2006.01); G06V 10/22 (2022.01); G06F 18/214 (2023.01); G06N 3/047 (2023.01); G06V 10/145 (2022.01);
U.S. Cl.
CPC ...
G01N 21/8806 (2013.01); G01J 3/2823 (2013.01); G01N 21/01 (2013.01); G01N 21/3581 (2013.01); G01N 21/8851 (2013.01); G01N 21/952 (2013.01); G01N 21/956 (2013.01); G06F 17/16 (2013.01); G06F 18/2148 (2023.01); G06N 3/04 (2013.01); G06N 3/047 (2023.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06T 7/0004 (2013.01); G06T 7/11 (2017.01); G06T 7/40 (2013.01); G06T 7/45 (2017.01); G06T 7/586 (2017.01); G06T 7/97 (2017.01); G06V 10/145 (2022.01); G06V 10/22 (2022.01); G06V 20/64 (2022.01); G06V 20/647 (2022.01); G01N 2021/8887 (2013.01); G06T 2207/10152 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

An artificial neural network-based method for selecting a surface type of an object includes receiving at least one object image, performing surface type identification on each of the at least one object image by using a first predictive model to categorize the object image to one of a first normal group and a first abnormal group, and performing surface type identification on each output image in the first normal group by using a second predictive model to categorize the output image to one of a second normal group and a second abnormal group.

Find Patent Forward Citations

Tsai, Kun-Yu. (2023). Artificial neural network-based method for selecting surface type of object (U.S. Patent No. 11650164). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/11650164

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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