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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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2025-01-01
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| Серии: | IEEE Access |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/10852306/ |
| Метки: |
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