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27 March 2024 Improving object detection algorithm for unmanned aerial vehicle aerial images based on YOLOv8
Pujie Zhao, Xia Ye, Hantao Xu, Zhangping Yang
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Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310509 (2024) https://doi.org/10.1117/12.3026332
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China
Abstract
In response to the challenges of diverse target scales, numerous similar objects, and target omissions and false positives resulting from object clustering in unmanned aerial vehicle (UAV) aerial image target identification, this paper introduces an improved UAV aerial image target identification algorithm called U-YOLOE . Within the initial YOLOv8 model's backbone network, a dual-route attention mechanism is incorporated to dynamically and sparsely filter out the least relevant features in the feature maps. This enhances the model's ability to capture key information in UAV aerial images, optimizing detector performance. Additionally, U-YOLOE employs WIoUv3 as the bounding box loss function, enhancing convergence speed and regression accuracy. Experimental results on the VisDrone2019 dataset reveal that, in comparison to the baseline model, U-YOLOE provides a 1% gain in Recall/%, a 1.2% gain in mAP0.5/%, and a 0.6% gain in mAP0.5:0.95%. Compared to other mainstream models, it demonstrates better performance in small object detection tasks for UAV aerial images.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Pujie Zhao, Xia Ye, Hantao Xu, and Zhangping Yang "Improving object detection algorithm for unmanned aerial vehicle aerial images based on YOLOv8", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310509 (27 March 2024); https://doi.org/10.1117/12.3026332
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KEYWORDS
Object detection
Data modeling
Mathematical optimization
Reflection
Sensors
Target detection
Target recognition
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