ARFNet: adaptive receptive field network for detecting insulator self-explosion defects

doi:10.1007/s11760-022-02186-3

	ARFNet: adaptive receptive field network for detecting insulator self-explosion defects
	Zhang, Ke 1,2; Qian, Shaowei 1,3; Zhou, Jianan 4; Xie, Chengjun 3; Du, Jianming 3; Yin, Tao 2
刊名	SIGNAL IMAGE AND VIDEO PROCESSING
	2022-04-15
关键词	Insulator self-explosion Object detection Adaptive receptive field network Attention mechanism Deep learning
ISSN号	1863-1703
DOI	10.1007/s11760-022-02186-3
通讯作者	Qian, Shaowei(qsw@mail.ustc.edu.cn) ; Du, Jianming(djming@iim.ac.cn)
英文摘要	Insulators are one of the critical components of high-altitude transmission lines. Insulator defects can lead to the failure of the power transmission system and even more severe consequences. Therefore, accurately locating and identifying insulator defects are particularly important. To address the problem of insulator information loss after insulation self-explosion and the large gap in insulator size, in this paper, we propose an effective and innovative module called adaptive receptive field network (ARFNet) to get proper context information for insulator self-explosion defects. ARFNet is an effective component that can be used in different networks to give the networks the ability to adapt the size of the receptive field through the attention mechanism. Besides, to further reduce the false detection rate, we also build a novel insulator dataset, including two categories of the whole insulator and the insulator self-explosion area. In addition, experiments show that our method can effectively improve detection accuracy and reduce the false detection rate.
资助项目	science and technology project of State Grid Corporation of China[5500-202140127A]
WOS研究方向	Engineering ; Imaging Science & Photographic Technology
语种	英语
出版者	SPRINGER LONDON LTD
WOS记录号	WOS:000782720500001
资助机构	science and technology project of State Grid Corporation of China
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/128691]
专题	中国科学院合肥物质科学研究院
通讯作者	Qian, Shaowei; Du, Jianming
作者单位	1.Univ Sci & Technol China, Hefei 230026, Peoples R China 2.Anhui NARI Jiyuan Power Grid Technol Co Ltd, State Grid Power Res Inst, Hefei 230088, Peoples R China 3.Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 4.Hunan Univ, Changsha 410000, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Ke,Qian, Shaowei,Zhou, Jianan,et al. ARFNet: adaptive receptive field network for detecting insulator self-explosion defects[J]. SIGNAL IMAGE AND VIDEO PROCESSING,2022.
APA	Zhang, Ke,Qian, Shaowei,Zhou, Jianan,Xie, Chengjun,Du, Jianming,&Yin, Tao.(2022).ARFNet: adaptive receptive field network for detecting insulator self-explosion defects.SIGNAL IMAGE AND VIDEO PROCESSING.
MLA	Zhang, Ke,et al."ARFNet: adaptive receptive field network for detecting insulator self-explosion defects".SIGNAL IMAGE AND VIDEO PROCESSING (2022).