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 TH1.R5: Classification Methods for SAR Data
Presentation Mode Virtual
Session Time Thu, 01 Oct, 12:00 - 14:00 UTC
Thu, 01 Oct, 20:00 - 22:00 China Standard Time (UTC +8)
Thu, 01 Oct, 14:00 - 16:00 Central Europe Time (UTC +2)
Thu, 01 Oct, 05:00 - 07:00 Pacific Daylight Time (UTC -7)
Session ChairsMihai Datcu, German Aerospace Center (DLR) and Florence Tupin, Telecom ParisTech
TH1.R5.1: LAND COVER CLASSIFICATION FOR POLSAR IMAGES BASED ON MIXTURE MODELS AND MRF
         Xiyun Liu; University of Science and Technology Beijing
         Junjun Yin; University of Science and Technology Beijing
         Jihua Zhang; Shanghai Electro Mechanical Engineering Institute
         Jian Yang; Tsinghua University
TH1.R5.2: SEMI-SUPERVISED CLASSIFICATION OF POLSAR DATA WITH MULTI-SCALE WEIGHTED GRAPH CONVOLUTIONAL NETWORK
         Shijie Ren; Xidian University
         Feng Zhou; Xidian University
TH1.R5.3: UNSUPERVISED LAND COVER CLASSIFICATION OF HYBRID POLSAR IMAGES USING DEEP NETWORK
         Ankita Chatterjee; Indian Institute of Technology Kharagpur
         Jayasree Saha; Indian Institute of Technology Kharagpur
         Jayanta Mukhopadhyay; Indian Institute of Technology Kharagpur
         Subhas Aikat; Indian Institute of Technology Kharagpur
         Arundhati Misra; Indian Institute of Technology Kharagpur
TH1.R5.4: COMPLEX-VALUED SPATIAL-SCATTERING SEPARATED ATTENTION NETWORK FOR POLSAR IMAGE CLASSIFICATION
         Zhaohao Fan; Nanjing University of Science and Technology
         Zexuan Ji; Nanjing University of Science and Technology
         Peng Fu; Nanjing University of Science and Technology
         Tao Wang; Nanjing University of Science and Technology
         Xiaobo Shen; Nanjing University of Science and Technology
         Quansen Sun; Nanjing University of Science and Technology
TH1.R5.5: A HYBRID AND EXPLAINABLE DEEP LEARNING FRAMEWORK FOR SAR IMAGES
         Zhongling Huang; Chinese Academy of Sciences
         Mihai Datcu; German Aerospace Center
         Zongxu Pan; Chinese Academy of Sciences
         Bin Lei; Chinese Academy of Sciences
TH1.R5.6: POLSAR SCENE CLASSIFICATION VIA LOW-RANK TENSOR-BASED MULTI-VIEW SUBSPACE REPRESENTATION
         Mengqian Chen; Xidian University
         Bo Ren; Xidian University
         Biao Hou; Xidian University
         Jocelyn Chanussot; University Grenoble Alpes
         Shuang Wang; Xidian University
         Xiangrong Zhang; Xidian University
         Wen Xie; Xi'an University of Posts and Telecommunications
TH1.R5.7: POLSAR IMAGE CLASSIFICATION BASED ON OPTIMAL FEATURE AND CONVOLUTION NEURAL NETWORK
         Ping Han; Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China
         Zetao Chen; Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China
         Yishuang Wan; Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China
         Zheng Cheng; Civil Aviation University of China
TH1.R5.8: ASSESSING FOREST/NON-FOREST SEPARABILITY USING SENTINEL-1 C-BAND SAR
         Johannes N. Hansen; University of Edinburgh
         Edward T. A. Mitchard; University of Edinburgh
         Stuart King; University of Edinburgh
TH1.R5.9: LEARNING RELATION BY GRAPH NEURAL NETWORK FOR SAR IMAGE FEW-SHOT LEARNING
         Rui Yang; Wuhan University
         Xin Xu; Wuhan University
         Xirong Li; Wuhan University
         Lei Wang; Wuhan University
         Fangling Pu; Wuhan University
TH1.R5.10: A NEURAL NETWORK APPROACH TO CLASSIFY MIXED CLASSES USING MULTI FREQUENCY SAR DATA
         Anjana Kukunuri; Indian Institute of Technology Roorkee
         Deepak Murugan; Indian Institute of Technology Roorkee
         Dharmendra Singh; Indian Institute of Technology Roorkee
TH1.R5.11: STACKED RANDOM FORESTS: MORE ACCURATE AND BETTER CALIBRATED
         Ronny Hänsch; German Aerospace Center (DLR)
TH1.R5.12: MULTI-VIEW CNN-LSTM NEURAL NETWORK FOR SAR AUTOMATIC TARGET RECOGNITION
         Chenwei Wang; UESTC
         Jifang Pei; UESTC
         Zhiyong Wang; UESTC
         Yuling Huang; UESTC
         Jianyu Yang; UESTC