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Swin-Transformer-YOLOv5 for lightweight hot-rolled steel strips surface defect detection algorithm

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成果类型:
期刊论文
作者:
Wang, Qiuyan;Dong, Haibing;Huang, Haoyue
通讯作者:
Dong, HB
作者机构:
[Wang, Qiuyan; Dong, Haibing; Dong, HB] Hunan Inst Technol, Sch Elect Informat Engn, Hengyang, Peoples R China.
[Huang, Haoyue] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.
通讯机构:
[Dong, HB ] H
Hunan Inst Technol, Sch Elect Informat Engn, Hengyang, Peoples R China.
语种:
英文
期刊:
PLOS ONE
ISSN:
1932-6203
年:
2024
卷:
19
期:
1
页码:
e0292082
基金类别:
National College Students' innovation and entrepreneurship training program [202211528034]
机构署名:
本校为其他机构
院系归属:
电气工程学院
摘要:
An essential industrial application is the examination of surface flaws in hot-rolled steel strips. While automatic visual inspection tools must meet strict real-time performance criteria for inspecting hot-rolled steel strips, their capabilities are constrained by the accuracy and processing speed of the algorithm used to identify defects. To solve the problems of poor detection accuracy, low detection efficiency, and unsuitability of low computing power platforms of the hot-rolled strip surface defect detection algorithm The Swin-Transformer-YOLOv5 model based on the improved one-stage detec...

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