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FEA-Swin: Foreground Enhancement Attention Swin Transformer Network for Accurate UAV-Based Dense Object Detection

文献类型：期刊论文

作者Xu, Wenyu1,2; Zhang, Chaofan2; Wang, Qi1,2; Dai, Pangda2
刊名SENSORS
出版日期2022-09-01
卷号22
关键词object detection aerial images transformer-based foreground enhancement attention improved bidirectional feature pyramid network
DOI10.3390/s22186993
通讯作者Zhang, Chaofan(zcfan@aiofm.ac.cn) ; Dai, Pangda(pddai@aiofm.ac.cn)
英文摘要UAV-based object detection has recently attracted a lot of attention due to its diverse applications. Most of the existing convolution neural network based object detection models can perform well in common object detection cases. However, due to the fact that objects in UAV images are spatially distributed in a very dense manner, these methods have limited performance for UAV-based object detection. In this paper, we propose a novel transformer-based object detection model to improve the accuracy of object detection in UAV images. To detect dense objects competently, an advanced foreground enhancement attention Swin Transformer (FEA-Swin) framework is designed by integrating context information into the original backbone of a Swin Transformer. Moreover, to avoid the loss of information of small objects, an improved weighted bidirectional feature pyramid network (BiFPN) is presented by designing the skip connection operation. The proposed method aggregates feature maps from four stages and keeps abundant information of small objects. Specifically, to balance the detection accuracy and efficiency, we introduce an efficient neck of the BiFPN network by removing a redundant network layer. Experimental results on both public datasets and a self-made dataset demonstrate the performance of our method compared to the state-of-the-art methods in terms of detection accuracy.
资助项目National Natural Science Foundation of China[62102395] ; Natural Science Foundation of Anhui Province of China[2108085QF277]
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
出版者MDPI
WOS记录号WOS:000857550700001
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Anhui Province of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/128988]  
专题中国科学院合肥物质科学研究院
通讯作者Zhang, Chaofan; Dai, Pangda
作者单位1.Univ Sci & Technol China, Grad Sch, Sci Isl Branch, Hefei 230026, Peoples R China
2.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Wenyu,Zhang, Chaofan,Wang, Qi,et al. FEA-Swin: Foreground Enhancement Attention Swin Transformer Network for Accurate UAV-Based Dense Object Detection[J]. SENSORS,2022,22.
APA Xu, Wenyu,Zhang, Chaofan,Wang, Qi,&Dai, Pangda.(2022).FEA-Swin: Foreground Enhancement Attention Swin Transformer Network for Accurate UAV-Based Dense Object Detection.SENSORS,22.
MLA Xu, Wenyu,et al."FEA-Swin: Foreground Enhancement Attention Swin Transformer Network for Accurate UAV-Based Dense Object Detection".SENSORS 22(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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