An improved lightweight YOLOv11 algorithm for weld surface defect detection

Abstract Industrial welding often exhibits some essential problems, such as unclear defect characteristics and complex background information. However, the existing defect detection models have relatively high costs and may be weak in weld surface defect detection. To address the problem, this paper...

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Hlavní autoři:	Runmei Zhang, Chenfei Pan, Zihua Chen, Jingwei Fan, Zhong Chen, Bin Yuan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2026-02-01
Edice:	Scientific Reports
Témata:	Deep learning Defect detection YOLOv11 PConv
On-line přístup:	https://doi.org/10.1038/s41598-026-41568-2
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