About this document
Vehicle Detection Using YOLOv5 and DeepSORT by Lukman Hakim is a document available to read on EtoBox.
This study explores the use of deep learning algorithms, specifically YOLOv5 and DeepSORT, for vehicle detection and counting to estimate traffic congestion. The authors trained a custom YOLOv5 dataset and achieved high precision and accuracy in detecting various vehicle types, demonstrating the potential for improved traffic management. The findings suggest that integrating these technologies can enhance traffic flow by identifying congested lanes and optimizing traffic light operations.
- Author
- Lukman Hakim
- Language
- EN