A Hybrid Learnable Fusion of ConvNeXt and Swin Transformer for Optimized Image Classification
Medical image classification often relies on CNNs to capture local details (e.g., lesions, nodules) or on transformers to model long-range dependencies. However, each paradigm alone is limited in addressing both fine-grained structures and broader anatomical context. We propose ConvTransGFusion, a h...
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| Autores principales: | , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2025-05-01
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| Colección: | IoT |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2624-831X/6/2/30 |
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