AutoMamba: Efficient Autonomous Driving Segmentation Model with Mamba

Semantic segmentation for autonomous driving demands balancing high-fidelity perception with real-time latency. While Transformers achieve state-of-the-art results, their quadratic complexity bottlenecks high-resolution processing. State Space Models (SSMs) like Mamba offer linear complexity but oft...

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Autors principals:	Haoran Sun, Zhensong Li, Shiliang Zhu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-04-01
Col·lecció:	Sensors
Matèries:	semantic segmentation autonomous driving state space models (SSM) mamba linear complexity real-time perception
Accés en línia:	https://www.mdpi.com/1424-8220/26/7/2227
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