Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition

doi:10.1007/s11063-018-9799-3

	Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition
	Chang, Wenkai1,2 ; Yang, Guodong1 ; Li, En1 ; Liang, Zize1
发表期刊	NEURAL PROCESSING LETTERS
ISSN	1370-4621
	2018-12-01
卷号	48 期号:3 页码:1789-1800
通讯作者	Chang, Wenkai(changwenkai2013@ia.ac.cn)
摘要	In this paper, we propose a learning-based real-time method to recognize and segment an overhead ground wire (OGW) from an image, which is mainly applied to the multi-scale features in a cluttered environment. The recognition and segmentation are implemented under the framework of conditional generative adversarial nets. The generator is an end-to-end convolutional neural network (CNN) with skip connection. The discriminator is a multi-stage CNN and learns the loss function to train the generator. The OGW is recognized and shown in the downsampling visual saliency map. Thus, the location and existence of OGW are verified, which is crucial for the detection in the cluttered environment with structural lines. Detailed experiments and comparisons are performed on real-world images to demonstrate that the proposed method significantly outperforms the traditional method. Additionally, the optimized network achieves approximately 200fps on a graphics card (GTX970) and 30fps on an embedded platform (Jetson TX1).
关键词	Power line recognition Conditional generative adversarial nets Power line inspection Hybrid robot
DOI	10.1007/s11063-018-9799-3
关键词[WOS]	POWER-LINE DETECTION ; MAINTENANCE
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61403374] ; National Natural Science Foundation of China[61403374]
项目资助者	National Natural Science Foundation of China
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000451460500031
出版者	SPRINGER
引用统计	被引频次：13[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/25714
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Chang, Wenkai
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Chang, Wenkai,Yang, Guodong,Li, En,et al. Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition[J]. NEURAL PROCESSING LETTERS,2018,48(3):1789-1800.
APA	Chang, Wenkai,Yang, Guodong,Li, En,&Liang, Zize.(2018).Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition.NEURAL PROCESSING LETTERS,48(3),1789-1800.
MLA	Chang, Wenkai,et al."Toward a Cluttered Environment for Learning-Based Multi-Scale Overhead Ground Wire Recognition".NEURAL PROCESSING LETTERS 48.3(2018):1789-1800.

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