DGGAT: Dual-branch gated graph attention transformer for high-accuracy semantic segmentation
Semantic segmentation requires both global context and fine-grained details, yet CNNs struggle with long-range dependencies and Transformers can under-represent low-level structure and be computationally heavy. We propose DGGAT, a dual-branch gated graph attention Transformer: a global branch models...
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| Autor principal: | |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Elsevier
2026-02-01
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| Col·lecció: | Alexandria Engineering Journal |
| Matèries: | |
| Accés en línia: | http://www.sciencedirect.com/science/article/pii/S1110016826000463 |
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