Cargando…
Learning Region-Based Attention Network for Traffic Sign Recognition
Traffic sign recognition in poor environments has always been a challenge in self-driving. Although a few works have achieved good results in the field of traffic sign recognition, there is currently a lack of traffic sign benchmarks containing many complex factors and a robust network. In this pape...
Autores principales: | Zhou, Ke, Zhan, Yufei, Fu, Dongmei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864033/ https://www.ncbi.nlm.nih.gov/pubmed/33498332 http://dx.doi.org/10.3390/s21030686 |
Ejemplares similares
-
Yolo-Based Traffic Sign Recognition Algorithm
por: Li, Ming, et al.
Publicado: (2022) -
Traffic Sign Recognition Based on the YOLOv3 Algorithm
por: Gong, Chunpeng, et al.
Publicado: (2022) -
Retracted: Yolo-Based Traffic Sign Recognition Algorithm
por: Intelligence and Neuroscience, Computational
Publicado: (2023) -
Hierarchical Novelty Detection for Traffic Sign Recognition
por: Ruiz, Idoia, et al.
Publicado: (2022) -
Traffic Sign Recognition with Deep Learning: Vegetation Occlusion Detection in Brazilian Environments
por: Dalborgo, Vanessa, et al.
Publicado: (2023)