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基于YOLOv5的无人机航拍小目标检测模型OA

A small target detection model for UAV aerial photography based on YOLOv5

中文摘要英文摘要

针对无人机小目标检测中漏检率高、检测成功率低等问题,提出一种基于YOLOv5的小目标检测算法.首先,分别在backbone结构和neck结构中,融合swin transformer模块,在减少计算成本的基础上,提高目标检测的准确率,能够适应无人机航拍小目标检测;其次,引入卷积注意力模块(convolutional block attention module,CBAM),以增强网络对小目标特征的关注度;最后,将原始损失函数CIOU替换为SIOU损…查看全部>>

In order to solve the problems of high missed detection rate and low detection success rate in UAV small target detection,a small target detection algorithm based on YOLOv5 was proposed.Firstly,the swin transformer module was integrated into the backbone structure and the neck structure respectively,which improved the accuracy of target detection on the basis of reducing the computation-al cost,and could adapt to the detection of small target in UAV aerial p…查看全部>>

石祥滨;赵芮同

沈阳航空航天大学 计算机学院,沈阳 110136沈阳航空航天大学 计算机学院,沈阳 110136

计算机与自动化

无人机航拍图像小目标检测YOLOv5transformer注意力机制损失函数

UAV aerial photographysmall target detectionYOLOv5transformerattention mecha-nismloss function

《沈阳航空航天大学学报》 2024 (2)

37-46,10

国家自然科学基金(项目编号:61170185)

10.3969/j.issn.2095-1248.2024.02.005

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