Improved YOLO11 model for weld surface defect detection

To address the problems of large scale variation, low contrast, and diverse overlapping of welding defects in complex backgrounds, an improved YOLO11 algorithm for weld surface defect detection was proposed. A feature extraction dilation-wise residual (DWR) module was introduced into the backbone ne...

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書目詳細資料

Principais autores:	Zhiying GAN, Chao WANG, Zhaomin JIA
格式:	Artigo
語言:	Chinês
出版:	Editorial Office of Transactions of the China Welding Institution, Welding Journals Publishing House 2026-05-01
叢編:	Hanjie xuebao
主題:	weld defect defect detection deep learning yolo11 model feature fusion
在線閱讀:	https://doi.org/10.12073/j.hjxb.20250726001
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