YOLOv11-LLR: An Enhanced Framework for Steel Surface Defect Detection in Industrial Settings
Steel surface defects in manufacturing are typically tiny, low-contrast, and boundary-ambiguous, especially under complex textures (e.g., rolling marks, crazing), poor illumination, and high noise. These characteristics cause frequent missed detections and localization errors, particularly for defec...
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| Asıl Yazarlar: | , , , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI AG
2026-05-01
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| Seri Bilgileri: | Applied Sciences |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/2076-3417/16/10/4609 |
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