Patch-sampled contrastive learning for dense prediction pretraining in metallographic images
Abstract The shapes, sizes, and distributions of microstructures determine the mechanical properties of alloy products, necessitating identification of microstructures in metallographic images during the manufacturing process. Previous studies demonstrated the success of deep learning in analyzing s...
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| Autors principals: | , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2025-12-01
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| Col·lecció: | Scientific Reports |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1038/s41598-025-32855-5 |
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