CDPNet: a deformable ProtoPNet for interpretable wheat leaf disease identification
IntroductionAccurate identification of wheat leaf diseases is crucial for food security, but existing prototype-based computer vision models struggle with the scattered nature of lesions in field conditions and lack interpretability. MethodsTo address this, we propose the Contrastive Deformable Prot...
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| Главные авторы: | , , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Frontiers Media S.A.
2025-11-01
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| Серии: | Frontiers in Plant Science |
| Предметы: | |
| Online-ссылка: | https://www.frontiersin.org/articles/10.3389/fpls.2025.1676798/full |
| Метки: |
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