Traffic Sign Recognition using YOLOv4
- Resource Type
- Conference
- Authors
- Yan, Wenjing; Yang, Guohua; Zhang, Wanlin; Liu, Lei
- Source
- 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) Intelligent Computing and Signal Processing (ICSP), 2022 7th International Conference on. :909-913 Apr, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Roads
Computational modeling
Signal processing algorithms
Clustering algorithms
Signal processing
Real-time systems
Safety
Convolutional neural network
Traffic Sign Recognition
YOLOv4
- Language
Traffic sign recognition can provide road information assessment and real-time safety early warning for safe driving of vehicles. The YOLOv4 model was adopted for traffic sign detection and recognition, and the K-means clustering algorithm is used to improve YOLOv4. A test was performed with the CCTSDB dataset. We achieved a 25.3fps and 90.42% mAP on the GTSDB dataset.