Study on the application of improved target detection algorithm for UAV in maritime search and rescue

Zhifang Chen; Qunyuan Chen

doi:10.1117/12.3045499

16 January 2025 Study on the application of improved target detection algorithm for UAV in maritime search and rescue

Zhifang Chen, Qunyuan Chen

Author Affiliations +

Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134474G (2025) https://doi.org/10.1117/12.3045499
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China

Abstract

To address the inefficiency of target detection algorithms for UAV in maritime search and rescue, an improved UAV target detection algorithm is proposed. First, the MobileNetV3 network is fused in the backbone network of YOLO-v5s to reduce the computational parameters of the algorithm model and make the algorithm easier to be deployed on the UAV embedded platform. Then, to address the problem of more interference factors in the detection image, CBAM (Convolutional Block Attention Module) attention mechanism is introduced to make the algorithm model pay more attention to the feature information of the trapped person, so as to improve the detection efficiency of the algorithm model. The experimental results show that the precision rate P of the improved algorithm reaches 0.966, the recall rate R reaches 0.937, and the mean average precision mAP_0.5 reaches 0.955, which is of high practical value and is expected to play an active role in the maritime search and rescue work.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhifang Chen and Qunyuan Chen "Study on the application of improved target detection algorithm for UAV in maritime search and rescue", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134474G (16 January 2025); https://doi.org/10.1117/12.3045499

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