Vehicle pedestrian detection method based on improved YOLOv5 algorithm
Vehicle pedestrian detection method based on improved YOLOv5 algorithm
- New search for: Chen, Zhao-hui
- New search for: Ling, Xiao-ming
- New search for: Wang, Gang
- New search for: Chen, Lei
- New search for: Chen, Zhao-hui
- New search for: Ling, Xiao-ming
Vehicle pedestrian detection is a key aspect in driver assistance systems, which need to accurately detect all vehicle pedestrian targets on the roadway in order to ensure driving safety. To solve the problem of low accuracy in vehicle pedestrian target detection, this paper proposes a vehicle pedestrian detection method based on the improved YOLOv5 algorithm. In this paper, the initial anchor boxes of the dataset are re-clustered by the K-means clustering algorithm, and the CIOU loss function and DIOU_nms, are applied to the YOLOv5 algorithm to improve the target recognition effect and reduce the false and missed detection rate of small targets. The experimental results show that the mAP@0.5 of the improved YOLOv5 algorithm is improved by 1.85%.
Document information
Vehicle pedestrian detection method based on improved YOLOv5 algorithm
Third International Conference on Signal Image Processing and Communication (ICSIPC 2023) ; 2023 ; Kunming, China
Proc. SPIE ; 12916
2023-10-20
Conference paper
Electronic Resource
English
Similar titles
Unmanned aerial vehicle landing method based on improved YOLOv5 algorithm
| European Patent Office | 2022
STD-Yolov5: a ship-type detection model based on improved Yolov5
| Taylor & Francis Verlag | 2024
Research on Improved YOLOv5 Vehicle Target Detection Algorithm in Aerial Images
| DOAJ | 2024