Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention

In respect of large noise interference of wheel tread and insufficient feature fusion of traditional detection algorithms, in order to achieve fast and accurate detection of wheel tread defects, a method for rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention was pr...

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Principais autores:	ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan
Format:	Artigo
Jezik:	Chinês
Izdano:	Editorial Department of Electric Drive for Locomotives 2022-11-01
Serija:	机车电传动
Teme:	defect detection wheel tread YOLO-v5 residual attention bidirectional feature pyramid
Online dostop:	http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2022.06.001
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