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:
Sep. 05, 2023

Filed:

Jul. 13, 2021
Applicant:

Advanced New Technologies Co., Ltd., Grand Cayman, KY;

Inventor:

Juan Xu, Hangzhou, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 16/55 (2019.01); G06T 7/00 (2017.01); G06F 16/58 (2019.01); G06N 5/04 (2023.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01); G06F 18/2113 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/40 (2022.01); G06V 20/00 (2022.01); G06V 20/20 (2022.01);
U.S. Cl.
CPC ...
G06F 16/55 (2019.01); G06F 16/5866 (2019.01); G06F 18/214 (2023.01); G06F 18/2113 (2023.01); G06F 18/24 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06T 7/0002 (2013.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 20/00 (2022.01); G06V 20/20 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/30248 (2013.01);
Abstract

A system is provided for identifying damages of a vehicle. During operation, the system can obtain a set of digital images associated with a set of tagged digital images as training data. Each tagged digital image in the set of tagged digital images may include at least one damage object. Based on the training data, the system can train a damage identification model by reducing noise associated with the damage object; generating a set of feature vectors for the training data; and using the set of feature vectors to optimize a set of parameters associated with the damage identification model to obtain a trained damage identification model. The system can then apply the trained damage identification model to obtain a damage category prediction result and determine a repair solution based on the damage category prediction result.


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