2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

My IGARSS 2020 Schedule

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Session Detail

Session Title FR1.R17: Machine Learning for Multitemporal Image Analysis
Presentation Mode Virtual
Session Time Fri, 02 Oct, 12:00 - 14:00 UTC
Fri, 02 Oct, 20:00 - 22:00 China Standard Time (UTC +8)
Fri, 02 Oct, 14:00 - 16:00 Central Europe Time (UTC +2)
Fri, 02 Oct, 05:00 - 07:00 Pacific Daylight Time (UTC -7)
Session ChairsFlavien Vernier, University Savoie Mont Blanc and Saloua Chlaily, University of Tromso, Norway
FR1.R17.1: S2-CGAN: SELF-SUPERVISED ADVERSARIAL REPRESENTATION LEARNING FOR BINARY CHANGE DETECTION IN MULTISPECTRAL IMAGES
         Jose Luis Holgado Alvarez; TU Berlin
         Mahdyar Ravanbakhsh; TU Berlin
         Begüm Demir; TU Berlin
FR1.R17.2: FLOOD MAPPING WITH SAR AND MULTI-SPECTRAL REMOTE SENSING IMAGES BASED ON WEIGHTED EVIDENTIAL FUSION
         Xi Chen; Peking University
         Yaokui Cui; Peking University
         Changjun Wen; Ministry of Civil Affairs of the People's Republic of China
         Mingxuan Zheng; Ministry of Civil Affairs of the People's Republic of China
         Yuan Gao; Ministry of Civil Affairs of the People's Republic of China
         Jing Li; Beijing Normal University
FR1.R17.3: A GPU ACCELERATED CONTOURLET METHOD FOR DETECTING CHANGES DUE TO FIRE USING REMOTE SENSING
         Rizwan Ahmed Ansari; North Carolina Central University
         Winnie Thomas; Indian Institute of Technology Bombay
         Rakesh Malhotra; North Carolina Central University
         Krishna Mohan Buddhiraju; Indian Institute of Technology Bombay
FR1.R17.4: HYPERSPECTRAL IMAGE CHANGE DETECTION BY SELF-SUPERVISED TENSOR NETWORK
         Feng Zhou; Donghua University
         Zhao Chen; Donghua University
FR1.R17.5: CHANGE DETECTION NETWORK OF NEARSHORE SHIPS FOR MULTI-TEMPORAL OPTICAL REMOTE SENSING IMAGES
         Jingyi Cao; Beijing University of Posts and Telecommunications
         Yanan You; Beijing University of Posts and Telecommunications
         Yuanyong Ning; Beijing University of Posts and Telecommunications
         Wenli Zhou; Beijing University of Posts and Telecommunications
FR1.R17.6: GEOSOT GRID REMOTE SENSING INTELLIGENT INTERPRETATION MODEL BASED ON FINE-TUNING RESNET-18: A CASE STUDY OF CONSTRUCTION LAND
         Daoye Zhu; Peking University
         Yi Yang; Peking University
         Weixin Zhai; Peking University
         Fuhu Ren; Peking University
         Chengqi Cheng; Peking University
         Min Huang; Wuhan University
FR1.R17.8: CHANGE OF GLACIAL LAKE IN KARAKORAM RANGE
         Fan Mou; University of Electronic Science and Technology of China
         Danyang Wang; University of Electronic Science and Technology of China
         Jiaxi Liu; University of Electronic Science and Technology of China
         Zezhong Zheng; University of Electronic Science and Technology of China
         Liming Jiang; Chinese Academy of Sciences
         Guoqing Zhou; Guilin University of Technology
         Fangrong Zhou; Yunnan Power Grid Co., Ltd.
FR1.R17.9: SIAMESE GENERATIVE ADVERSARIAL NETWORK FOR CHANGE DETECTION UNDER DIFFERENT SCALES
         Mengxi Liu; Sun Yat-sen University
         Qian Shi; Sun Yat-sen University
         Penghua Liu; Sun Yat-sen University
         Cheng Wan; Sun Yat-sen University
FR1.R17.10: A DEEP GENERALIZED CORRELATION NETWORK FOR BITEMPORAL IMAGE CHANGE DETECTION
         Rongfang Wang; Xidian University
         Weidong Wang; Xidian University
         Jia-Wei Chen; Xidian University
         Licheng Jiao; Xidian University
         Hongxia Hao; Xidian University
FR1.R17.11: A LIGHTWEIGHT CONVOLUTIONAL NEURAL NETWORK FOR BITEMPORAL IMAGE CHANGE DETECTION
         Rongfang Wang; Xidian University
         Fan Ding; Xidian University
         Jia-Wei Chen; Xidian University
         Licheng Jiao; Xidian University
         Liang Wang; Xidian University
FR1.R17.12: PROPAGATED UNCERTAINTY FOR HORIZONTAL GROUND MOTION DERIVED FROM MULTI-TEMPORAL DIGITAL ELEVATION MODELS
         Preston Hartzell; University of Houston
         Craig Glennie; University of Houston