Research on target recognition technology based on improved YOLOv5

Lu-lu Fang; Yang Zhang; Tao Jing; Hai-rong Hu

doi:10.1117/12.3000843

9 August 2023 Research on target recognition technology based on improved YOLOv5

Lu-lu Fang, Yang Zhang, Tao Jing, Hai-rong Hu

Proceedings Volume 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023); 1278211 (2023) https://doi.org/10.1117/12.3000843
Event: Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Aiming at the problem of low detection accuracy in traditional UAV target recognition, an improved YOLOv5 target recognition method is proposed. The loss function of YOLOv5 is improved, and the CIoU loss function is used instead of the GIoU loss function used by YOLOv5 to optimize the training model. The accuracy of the algorithm is improved, and a more accurate identification of the target is realized. The experimental results show that the mAP value of the model trained on the aviation dataset NWPU VHR-10 by the improved YOLOv5 algorithm reaches 93.33%, which is 4% higher than the original YOLOv5 algorithm.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lu-lu Fang, Yang Zhang, Tao Jing, and Hai-rong Hu "Research on target recognition technology based on improved YOLOv5", Proc. SPIE 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 1278211 (9 August 2023); https://doi.org/10.1117/12.3000843

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