TSingNet: Scale-aware and context-rich feature learning for traffic sign detection and recognition in the wild
Work
Year: 2021
Type: article
Source: Neurocomputing
Institutions China University of Geosciences, Shenzhen Academy of Robotics, University College London, Chinese University of Hong Kong, Shenzhen
Cites: 47
Cited by: 46
Related to: 10
FWCI: 4.55
Citation percentile (by year/subfield): 80.58
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Sustainable Development Goal Sustainable cities and communities
Open Access status: green