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Title:
DEFECT POINT IDENTIFICATION METHOD BASED ON DEEP LEARNING NETWORK
Document Type and Number:
WIPO Patent Application WO/2023/019636
Kind Code:
A1
Abstract:
A defect point identification method based on a deep learning network. The method first process an image having a defect by using a Resnet-50 feature extraction network, extracts features of the defect, and then detects and identifies the defect by using an enhanced transformer network. By enhancing the transformer network module of a DETR network, the method can detect the defect more accurately while improving the speed.

Inventors:
WANG HUIYAN (CN)
JIANG HUAN (CN)
Application Number:
PCT/CN2021/115494
Publication Date:
February 23, 2023
Filing Date:
August 31, 2021
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Assignee:
UNIV ZHEJIANG GONGSHANG (CN)
International Classes:
G06N3/04; G06N3/08
Foreign References:
CN111899224A2020-11-06
CN111681228A2020-09-18
CN111260614A2020-06-09
US20190163904A12019-05-30
Attorney, Agent or Firm:
HANGZHOU AOCHUANG INTELLECTUAL PROPERTY AGENCY CO., LTD. (CN)
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