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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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Chinês |
| Publicado em: |
Editorial Office of Transactions of the China Welding Institution, Welding Journals Publishing House
2026-05-01
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| coleção: | Hanjie xuebao |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.12073/j.hjxb.20250726001 |
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