An efficient and lightweight algorithm for detecting surface defects of steel based on SCCI-YOLO
Abstract Steel is a crucial raw material in the industrial sector, and its surface defects significantly impact product quality. These defects are diverse in type, complex in shape, uneven in distribution, and varied in size, posing substantial challenges for performance and detection. Addressing th...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2025-10-01
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| Col·lecció: | Scientific Reports |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1038/s41598-025-20154-y |
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