YOLO-BS: a traffic sign detection algorithm based on YOLOv8
Abstract
Traffic signs are pivotal components of traffic management, ensuring the regulation and safety of road traffic. However, existing detection methods often suffer from low accuracy and poor real-time performance in dynamic road environments. This paper reviews traditional traffic sign detection methods and introduces an enhanced detection algorithm (YOLO-BS) based on YOLOv8 (You Only Look Once version 8). This algorithm addresses the challenges of complex backgrounds and small-sized detection targets in traffic sign images. A small object detection layer was incorporated into the YOLOv8 framework to enrich feature extraction. Additionally, a bidirectional feature pyramid network (BiFPN) was integrated into the…
Citation impact
- FWCI
- 53.81
- Percentile
- 100%
- References
- 20
Authors
3- HZHong ZhangCorresponding
Inner Mongolia University
- MLMingyin Liang
Inner Mongolia University
- YWY. Wang
Inner Mongolia University
Topics & keywords
- Computer science
- Sign (mathematics)
- Algorithm
- Data mining
- Mathematics