Cargando…
Research on Road Scene Understanding of Autonomous Vehicles Based on Multi-Task Learning
Road scene understanding is crucial to the safe driving of autonomous vehicles. Comprehensive road scene understanding requires a visual perception system to deal with a large number of tasks at the same time, which needs a perception model with a small size, fast speed, and high accuracy. As multi-...
Autores principales: | Guo, Jinghua, Wang, Jingyao, Wang, Huinian, Xiao, Baoping, He, Zhifei, Li, Lubin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346996/ https://www.ncbi.nlm.nih.gov/pubmed/37448087 http://dx.doi.org/10.3390/s23136238 |
Ejemplares similares
-
Autonomous Vehicle Dataset with Real Multi-Driver Scenes and Biometric Data
por: Rosique, Francisca, et al.
Publicado: (2023) -
Explainable AI in Scene Understanding for Autonomous Vehicles in Unstructured Traffic Environments on Indian Roads Using the Inception U-Net Model with Grad-CAM Visualization
por: Kolekar, Suresh, et al.
Publicado: (2022) -
Research on the visual image-based complexity perception method of autonomous navigation scenes for unmanned surface vehicles
por: Shi, Binghua, et al.
Publicado: (2022) -
Occlusion-Free Road Segmentation Leveraging Semantics for Autonomous Vehicles
por: Wang, Kewei, et al.
Publicado: (2019) -
Research on Recognition of Road Hypnosis in the Typical Monotonous Scene
por: Shi, Huili, et al.
Publicado: (2023)