Cargando…
Research on a Traffic Sign Recognition Method under Small Sample Conditions
Traffic signs are updated quickly, and there image acquisition and labeling work requires a lot of manpower and material resources, so it is difficult to provide a large number of training samples for high-precision recognition. Aiming at this problem, a traffic sign recognition method based on FSOD...
Autores principales: | Zhang, Xiao, Zhang, Zhenyu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255601/ https://www.ncbi.nlm.nih.gov/pubmed/37299816 http://dx.doi.org/10.3390/s23115091 |
Ejemplares similares
-
Yolo-Based Traffic Sign Recognition Algorithm
por: Li, Ming, et al.
Publicado: (2022) -
Hierarchical Novelty Detection for Traffic Sign Recognition
por: Ruiz, Idoia, et al.
Publicado: (2022) -
Improved Traffic Sign Detection and Recognition Algorithm for Intelligent Vehicles
por: Cao, Jingwei, et al.
Publicado: (2019) -
Traffic Sign Recognition Based on the YOLOv3 Algorithm
por: Gong, Chunpeng, et al.
Publicado: (2022) -
Recent Advances in Traffic Sign Recognition: Approaches and Datasets
por: Lim, Xin Roy, et al.
Publicado: (2023)