EMSFomer: Efficient Multi-Scale Transformer for Real-Time Semantic Segmentation
Transformer-based models have achieved impressive performance in semantic segmentation in recent years. However, the multi-head self-attention mechanism in Transformers incurs significant computational overhead and becomes impractical for real-time applications due to its high complexity and large l...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2025-01-01
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| Colecção: | IEEE Access |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/10852306/ |
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