Research on vehicle detection algorithm based on YOLOv5

Yutong Guo

doi:10.1117/12.3051058

27 September 2024 Research on vehicle detection algorithm based on YOLOv5

Yutong Guo

Proceedings Volume 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024); 132810K (2024) https://doi.org/10.1117/12.3051058
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning, 2024, Zhengzhou, China

Abstract

With the surge of 5G technology, research on intelligent transportation systems has emerged as a forefront area, with vehicle detection technology at its core. This paper delves into vehicle detection utilizing YOLOv5, analyzing its performance through key metrics like training/validation losses, precision, recall, and mAP. The study highlights YOLOv5's superiority in vehicle detection, balancing swiftness with high accuracy and robustness. This work reinforces deep learning-based vehicle detection and presents valuable insights for future research endeavors.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yutong Guo "Research on vehicle detection algorithm based on YOLOv5", Proc. SPIE 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024), 132810K (27 September 2024); https://doi.org/10.1117/12.3051058

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