Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 9, 1308(2025)
Aerial small target detection algorithm based on context collaborative perception
Aiming at the problem of low detection accuracy of small targets caused by large scale change and complex background in aerial photography, a detection algorithm based on multi-scale collaborative perception of context is proposed. Firstly, a lightweight multi-scale enhancement module (LMEM) is constructed to activate local significance information with attention mechanism to enhance feature capture capability of small targets. Secondly, the context-driven cross-level feature fusion architecture module (CCFFAM) is designed. The integration of receptive field attention convolution and dynamic sampling technology realizes multi-layer feature space-channel dual alignment and adaptive weighted fusion to enhance feature fusion capability. Finally, the scale distribution of the detection head was reconstructed, and the original loss function was replaced with Focaler-CIoU to optimize the bounding box regression process, ensuring that the model is lightweight while having a high detection efficiency. Experiments on VisDrone2019 and DOTAv1 data sets show that the proposed method reduces the number of model parameters by 27.9% (2.17M) compared with the original model, and the mAP increases by 5.3% and 1.4% respectively, which verifies that the algorithm has a good detection effect.
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Luxia YANG, Zekai LIU, Hongrui ZHANG, Yongjie MA. Aerial small target detection algorithm based on context collaborative perception[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(9): 1308
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Received: Apr. 25, 2025
Accepted: --
Published Online: Sep. 25, 2025
The Author Email: Hongrui ZHANG (zhanghongrui@tynu.edu.cn)