Cargando…
Occlusion-Free Road Segmentation Leveraging Semantics for Autonomous Vehicles
The deep convolutional neural network has led the trend of vision-based road detection, however, obtaining a full road area despite the occlusion from monocular vision remains challenging due to the dynamic scenes in autonomous driving. Inferring the occluded road area requires a comprehensive under...
Autores principales: | Wang, Kewei, Yan, Fuwu, Zou, Bin, Tang, Luqi, Yuan, Quan, Lv, Chen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864472/ https://www.ncbi.nlm.nih.gov/pubmed/31671547 http://dx.doi.org/10.3390/s19214711 |
Ejemplares similares
-
Semantic Segmentation with Transfer Learning for Off-Road Autonomous Driving
por: Sharma, Suvash, et al.
Publicado: (2019) -
Semantic Segmentation Leveraging Simultaneous Depth Estimation
por: Sun, Wenbo, et al.
Publicado: (2021) -
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml
por: Ghielmetti, Nicolò, et al.
Publicado: (2022) -
SemanticDepth: Fusing Semantic Segmentation and Monocular Depth Estimation for Enabling Autonomous Driving in Roads without Lane Lines
por: Palafox, Pablo R., et al.
Publicado: (2019) -
Understanding common human driving semantics for autonomous vehicles
por: Xia, Yingji, et al.
Publicado: (2023)