A hybrid convolution and attention-based framework with visual explanation for fruit disease identification
Abstract The objective of this study is to create a highly accurate and interpretable deep learning (DL) model for the multi-class classification of fruit using convolutional and transformer architectures. The classification performance can be enhanced by making sure that the used technique is expla...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Portfolio
2026-03-01
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| Schriftenreihe: | Scientific Reports |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1038/s41598-026-42135-5 |
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