A small target detection method for UAV aerial images based on improved YOLOv5

Hao Yue; Chenyang Yan; Tao Mi; Songsong Yan; Xin He

doi:10.1117/12.3013250

29 November 2023 A small target detection method for UAV aerial images based on improved YOLOv5

Hao Yue, Chenyang Yan, Tao Mi, Songsong Yan, Xin He

Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 129370F (2023) https://doi.org/10.1117/12.3013250
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore

Abstract

There are many instances of small and medium-sized targets in drone aerial images, and existing detection algorithms are prone to missed and false detections during the detection process. To address this issue, A small target detection method based on improved YOLOv5 in UAV aerial images are proposed. Firstly, the bilinear interpolation upsampling method is used in the feature fusion section to reduce the loss of feature information during the upsampling process. Then, a small target detection layer of size 160 is added to locate and recognize small targets using shallow feature information, reducing the missed detection rate. Finally, three CBAM attention mechanism modules were added to improve the accuracy of the algorithm. On the VisDrone2019 dataset, the improved algorithm improved mAP by 2.1% compared to Algorithm YOLOv5, effectively completing small object detection tasks.

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

Citation Download Citation

Hao Yue, Chenyang Yan, Tao Mi, Songsong Yan, and Xin He "A small target detection method for UAV aerial images based on improved YOLOv5", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 129370F (29 November 2023); https://doi.org/10.1117/12.3013250

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KEYWORDS

Object detection

Detection and tracking algorithms

Small targets

Target detection

Interpolation

Data modeling

Unmanned aerial vehicles

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