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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TH2.MM-3.2

Re-DLinkNet: Based on DLinkNet and ReNet for Road Extraction from High Resolution Satellite Imagery

Yuchuan Wang, Ling Tong, Jiang Wen, Fanghong Xiao, Yaqi Gao, Liubei He, University of Electronic Science and Technology of China, China; Dingmao Li, Shanxi Luneng Hequ Electric Coal Development Co. Ltd, China
Session:
Object Extraction in Optical Images
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Thu, 15 Jul, 11:05-11:10 (UTC)
Thu, 15 Jul, 13:05-13:10 Central Europe Summer Time (UTC +2)
Thu, 15 Jul, 19:05-19:10 China Standard Time (UTC +8)
Thu, 15 Jul, 07:05-07:10 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Leonid Shumilo, Space Research Institute NASU-SSAU and Gencer Sumbul, TU Berlin
Session Manager:
Sina Mohammadi
Presentation
Discussion
Resources
Session TH2.MM-3
TH2.MM-3.1: AN IMPROVED DEEP-LEARNING MODEL FOR ROAD EXTRACTION FROM VERY-HIGH-RESOLUTION REMOTE SENSING IMAGES
Wangyao Shen, Yunping Chen, Yuanlei Cheng, Kangzhuo Yang, Xiang Guo, University of Electronic Science and Technology of China, China; Yuan Sun, Chinese Academy of Sciences, China; Yan Chen, University of Electronic Science and Technology of China, China
TH2.MM-3.2: Re-DLinkNet: Based on DLinkNet and ReNet for Road Extraction from High Resolution Satellite Imagery
Yuchuan Wang, Ling Tong, Jiang Wen, Fanghong Xiao, Yaqi Gao, Liubei He, University of Electronic Science and Technology of China, China; Dingmao Li, Shanxi Luneng Hequ Electric Coal Development Co. Ltd, China
TH2.MM-3.3: A CNN WITH MULTISCALE CONVOLUTION FOR HYPERSPECTRAL IMAGE CLASSIFICATION USING TARGET-PIXEL-ORIENTATION SCHEME
Jayasree Saha, Yuvraj Khanna, Jayanta Mukhopadhyay, Indian Institute of Technology Kharagpur, India
TH2.MM-3.4: IMPROVING MORE INSTANCE SEGMENTATION AND BETTER OBJECT DETECTION IN REMOTE SENSING IMAGERY BASED ON CASCADE MASK R-CNN
Durga Kumar, Xiaoling Zhang, University of Electronic Science and Technology of China, China
TH2.MM-3.5: V2RNET: AN UNSUPERVISED SEMANTIC SEGMENTATION ALGORITHM FOR REMOTE SENSING IMAGES VIA CROSS-DOMAIN TRANSFER LEARNING
Danpei Zhao, Jiayi Li, Bo Yuan, Zhenwei Shi, Image Processing Center, School of Astronautics, Beihang University, China
TH2.MM-3.6: U-NET MODEL FOR LOGGING DETECTION BASED ON THE SENTINEL-1 AND SENTINEL-2 DATA
Leonid Shumilo, Nataliia Kussul, Mykola Lavreniuk, Space Research Institute NASU-SSAU, Ukraine
TH2.MM-3.7: DAMAGED ROAD EXTRACTION BASED ON SIMULATED POST-DISASTER REMOTE SENSING IMAGES
Yansong Huang, Haocai Wei, Junli Yang, Ming Wu, Beijing University of Posts and Telecommunications, China

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