Institute of Computing Technology, Chinese Academy IR
AD-YOLOv5s based UAV detection for low altitude security | |
Shang, Yuanfeng1,2,3; Liu, Chang1,2,3; Qiu, Dawei1,2,3,5; Zhao, Zixu1,2,3,4; Wu, Ruikang1,2,3; Tang, Shuyuan1,4 | |
2023 | |
发表期刊 | INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES |
ISSN | 1756-8293 |
卷号 | 15页码:19 |
摘要 | UAV (Unmanned Aerial Vehicle) black flight at low altitude could cause serious safety risks. Consequently, it is crucial to detect and manage low altitude small UAVs. The existing methods of low altitude small UAV detection suffer from problems such as high false alarm rate, and poor real-time performance. In order to solve the above problems, we present a novel approach, named AD-YOLOv5s, to achieve low altitude small UAV detection with high precision and high real-time performance. Firstly, the feature enhancement method is used to expand the dataset. We optimize the model feature fusion, the prediction head structure, and the loss function. Based on the CBAM (Convolutional Block Attention Module) attention mechanism, feature enhancement is performed to improve the detection accuracy. Secondly, the ghost module and depthwise separable convolution are used to reduce the number of parameters of the model, and we propose the method of lightweight design of model to improve the detection speed. Compared with the YOLOv5s model, the experiment result shows that our proposed AD-YOLOv5s model improves the value of mAP by 2.2% and the value of Recall by 1.8%, reduces the value of GFLOPs by 29.9% and parameters by 38.8%, and achieves 27.6 FPS when the proposed model deploy on a low-cost edge computing device (jetson nano). |
关键词 | Low Altitude Security object detection embedded deployment deep learning UAV |
DOI | 10.1177/17568293231190017 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Ramp;D Program of China[2022YFC3320800] ; Zhejiang Provincial Key Ramp;D Plan of China[2021C01040] |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Aerospace |
WOS记录号 | WOS:001037734500001 |
出版者 | SAGE PUBLICATIONS LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/21282 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Qiu, Dawei |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol,State Key Lab Processors,CAS, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Shang, Yuanfeng,Liu, Chang,Qiu, Dawei,et al. AD-YOLOv5s based UAV detection for low altitude security[J]. INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES,2023,15:19. |
APA | Shang, Yuanfeng,Liu, Chang,Qiu, Dawei,Zhao, Zixu,Wu, Ruikang,&Tang, Shuyuan.(2023).AD-YOLOv5s based UAV detection for low altitude security.INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES,15,19. |
MLA | Shang, Yuanfeng,et al."AD-YOLOv5s based UAV detection for low altitude security".INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES 15(2023):19. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论