The experimental environment.

In the field of UAV aerial image processing, ensuring accurate detection of tiny targets is essential. Current UAV aerial image target detection algorithms face challenges such as low computational demands, high accuracy, and fast detection speeds. To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. Second, a lightweight cross-scale feature pyramid network (LC-FPN) is employed to further enrich feature information, integrate multi-level feature maps, and provide more comprehensive semantic information. Finally, to increase model training speed and achieve greater efficiency, we propose a lightweight, detail-enhanced, shared convolution detection head (LDSCD-Head) to optimize the original detection head. Moreover, we present different scale versions of the LCFF-Net algorithm to suit various deployment environments. Empirical assessments conducted on the VisDrone dataset validate the efficacy of the algorithm proposed. Compared to the baseline-s model, the LCFF-Net-n model outperforms baseline-s by achieving a 2.8% increase in the mAP50 metric and a 3.9% improvement in the mAP50–95 metric, while reducing parameters by 89.7%, FLOPs by 50.5%, and computation delay by 24.7%. Thus, LCFF-Net offers high accuracy and fast detection speeds for tiny target detection in UAV aerial images, providing an effective lightweight solution.

在无人机（UAV）航拍图像处理领域，精准检测微小目标是核心刚需。当前无人机航拍目标检测算法面临的核心挑战在于如何同时兼顾低计算开销、高精度与快速检测的性能要求。为此，本文提出一种改进型轻量化算法LCFF-Net。首先，本文提出LFERELAN模块，旨在强化微小目标特征提取能力并优化计算资源利用率。其次，采用轻量化跨尺度特征金字塔网络（cross-scale feature pyramid network，缩写LC-FPN），进一步丰富特征信息、整合多层级特征图以提供更全面的语义信息。最后，为提升模型训练速度并实现更高运行效率，本文提出一种轻量化细节增强型共享卷积检测头（LDSCD-Head），以优化原始检测头结构。此外，本文还推出了不同算力适配版本的LCFF-Net算法，以适配多样化的部署场景。在VisDrone数据集上开展的实证评估验证了本文所提算法的有效性。相较于基线模型baseline-s，LCFF-Net-n模型的mAP50指标提升2.8%，mAP50-95指标提升3.9%；同时参数规模降低89.7%，浮点运算量（FLOPs）减少50.5%，计算延迟降低24.7%。综上，LCFF-Net可在无人机航拍图像微小目标检测任务中实现高精度与快速检测的平衡，为该领域提供了一种高效的轻量化解决方案。