QQ客服 官方微博 反馈留言

	RoadNet: Learning to Comprehensively Analyze Road Networks in Complex Urban Scenes from High-Resolution Remotely Sensed Images
	Liu, Yahui; Yao, Jian; Lu, Xiaohu; Xia, Menghan; Wang, Xingbo; Liu, Yuan
刊名	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
	2019
卷号	57期号:4
关键词	Benchmark data set bilinear blending centerline extraction convolutional neural networks (CNNs) edge detection image segmentation loss function road network extraction user interaction
ISSN号	0196-2892
DOI	10.1109/TGRS.2018.2870871
URL标识	查看原文
收录类别	SCIE
语种	英语
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4215316
专题	武汉大学
推荐引用方式 GB/T 7714	Liu, Yahui,Yao, Jian,Lu, Xiaohu,et al. RoadNet: Learning to Comprehensively Analyze Road Networks in Complex Urban Scenes from High-Resolution Remotely Sensed Images[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2019,57(4).
APA	Liu, Yahui,Yao, Jian,Lu, Xiaohu,Xia, Menghan,Wang, Xingbo,&Liu, Yuan.(2019).RoadNet: Learning to Comprehensively Analyze Road Networks in Complex Urban Scenes from High-Resolution Remotely Sensed Images.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,57(4).
MLA	Liu, Yahui,et al."RoadNet: Learning to Comprehensively Analyze Road Networks in Complex Urban Scenes from High-Resolution Remotely Sensed Images".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 57.4(2019).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

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。