Application Research on Lightweight Vehicle Detection Based on YOLO
- Resource Type
- Conference
- Authors
- Peng, Jun; He, Yuanmin; Jin, Shangzhu; Dai, Haojun; Peng, Fei; Wu, Xiao; Wu, Yu
- Source
- IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society Industrial Electronics Society, IECON 2023- 49th Annual Conference of the IEEE. :1-6 Oct, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Knowledge engineering
Industrial electronics
Pedestrians
Vehicle detection
Roads
Neck
Task analysis
YOLOvS
vehicle detection
lightweight
GSConv
C2f
- Language
- ISSN
- 2577-1647
A lightweight object detection algorithm based on YOLOv5 is proposed to address the problem of deploying detection models for traffic targets. This method was proposed to reduce the number of channels in the backbone and introduced GSConv to improve performance. At the same time, GSConv was improved to cut the parameters. The C3 module was replaced in the Neck with C2f to obtain more comprehensive gradient flow information. Finally, the model parameters are only 1.41M. Experiment on BDD100K public traffic dataset shows that the lightweight model reduces the number of parameters while losing a small amount of Recalls, and its performance is better than mainstream lightweight networks.