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.R3: Feature Reduction by Neural and/or Spatial Characterization I
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 ChairsNaoto Yokoya, RIKEN Center for Advanced Intelligence Project (AIP) and Uta Heiden, German Aerospace Center (DLR)
TH1.R3.1: EDGE-DRIVEN OBJECT MATCHING FOR UAV IMAGES AND SATELLITE SAR IMAGES
         Ruixiang Zhang; Wuhan University
         Fang Xu; Wuhan University
         Huai Yu; Wuhan University
         Wen Yang; Wuhan University
         Heng-Chao Li; Southwest Jiaotong University
TH1.R3.2: GRAPH-BASED MICRO-SEISMIC SIGNAL CLASSIFICATION WITH AN OPTIMISED FEATURE SPACE
         Jiangfeng Li; University of Strathclyde
         Cheng Yang; York University
         Vladimir Stankovic; University of Strathclyde
         Lina Stankovic; University of Strathclyde
         Stella Pytharouli; University of Strathclyde
TH1.R3.3: FEEDBACK NEURAL NETWORK BASED SUPER-RESOLUTION OF DEM FOR GENERATING HIGH FIDELITY FEATURES
         Ashish Kubade; International Institute of Information Technology Hyderabad
         Avinash Sharma; International Institute of Information Technology Hyderabad
         K. S. Rajan; International Institute of Information Technology Hyderabad
TH1.R3.4: MANIFOLD LEARNING WITH HIGH DIMENSIONAL MODEL REPRESENTATIONS
         Gülşen Taşkın; İstanbul Technical University
         Gustau Camps-Valls; Universitat de Vale ́ncia
TH1.R3.5: A TENSOR DECOMPOSITION METHOD FOR UNSUPERVISED FEATURE LEARNING ON SATELLITE IMAGERY
         Golnoosh Dehghanpoor; Washington University in St. Louis
         Michael Frachetti; Washington University in St. Louis
         Brendan Juba; Washington University in St. Louis
TH1.R3.6: SELF-SUPERVISED REMOTE SENSING IMAGE RETRIEVAL
         Kane Walter; University of New South Wales
         Matthew Gibson; University of New South Wales
         Arcot Sowmya; University of New South Wales
TH1.R3.7: BAND-WISE MULTI-SCALE CNN ARCHITECTURE FOR REMOTE SENSING IMAGE SCENE CLASSIFICATION
         Jian Kang; Technische Universität Berlin
         Begüm Demir; Technische Universität Berlin
TH1.R3.8: MULTIFRACTAL FEATURES FOR LAND USE CLASSIFICATION
         Anna Wawrzaszek; Centrum Badań Kosmicznych Polskiej Akademii Nauk
         Wojciech Drzewiecki; AGH University of Science and Technology
         Michał Krupiński; Centrum Badań Kosmicznych Polskiej Akademii Nauk
         Małgorzata Jenerowicz; Centrum Badań Kosmicznych Polskiej Akademii Nauk
         Sebastian Aleksandrowicz; Centrum Badań Kosmicznych Polskiej Akademii Nauk
TH1.R3.9: EXTRACTING VEHICLES IN POINT CLOUDS OF UNDERGROUND PARKING LOTS BASED ON GRAPH CONVOLUTION
         Di Liu; Xiamen University
         Zhipeng Luo; Xiamen University
         Zhenlong Xiao; Xiamen University
         Jonathan Li; Xiamen University; University of Waterloo
TH1.R3.10: A HYBRID MODEL BASED ON FUSED FEATURES FOR DETECTION OF NATURAL DISASTERS FROM SATELLITE IMAGES
         Tanu Gupta; Indian Institute of Technology Roorkee
         Sudip Roy; Indian Institute of Technology Roorkee
TH1.R3.11: SYMMETRIC SCATTERING MODEL BASED FEATURE EXTRACTION FROM GENERAL COMPACT POLARIMETRIC SAR IMAGERY
         Junjun Yin; University of Science and Technology Beijing
         Jian Yang; Tsinghua University
TH1.R3.12: CNN-BASED BUILDING FOOTPRINT DETECTION FROM SENTINEL-1 SAR IMAGERY
         Andrea Rapuzzi; A-SIGN
         Cristiano Nattero; FadeOut Software srl
         Ramona Pelich; Luxembourg Institute of Science and Technology (LIST)
         Marco Chini; Luxembourg Institute of Science and Technology (LIST)
         Paolo Campanella; FadeOut Software srl