Robust Fusion of 4-D Radar and Camera for All-Weather Perception in Autonomous Driving
Robust perception in autonomous driving, especially under adverse weather conditions, remains a significant challenge. While 4D imaging radar offers a cost-effective and weather-resilient alternative to LiDAR, its data is inherently noisy. The noise not only corrupts single-frame perception but also...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2026-01-01
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| coleção: | IEEE Open Journal of Intelligent Transportation Systems |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/11578084/ |
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