TH1.R3.8

MULTIFRACTAL FEATURES FOR LAND USE CLASSIFICATION

Anna Wawrzaszek, Centrum Badań Kosmicznych Polskiej Akademii Nauk, Poland; Wojciech Drzewiecki, AGH University of Science and Technology, Poland; Michał Krupiński, Małgorzata Jenerowicz, Sebastian Aleksandrowicz, Centrum Badań Kosmicznych Polskiej Akademii Nauk, Poland

Session:
Feature Reduction by Neural and/or Spatial Characterization I

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Thu, 1 Oct, 13:10-13:20 (UTC)
Thu, 1 Oct, 21:10-21:20 China Standard Time (UTC +8)
Thu, 1 Oct, 15:10-15:20 Central Europe Summer Time (UTC +2)
Thu, 1 Oct, 06:10-06:20 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Naoto Yokoya, RIKEN Center for Advanced Intelligence Project (AIP) and Uta Heiden, German Aerospace Center (DLR)
Session Manager:
Tianlin Wang

Presentation

Discussion

Resources

Session

TH1.R3.1: EDGE-DRIVEN OBJECT MATCHING FOR UAV IMAGES AND SATELLITE SAR IMAGES
Ruixiang Zhang, Fang Xu, Huai Yu, Wen Yang, Wuhan University, China; Heng-Chao Li, Southwest Jiaotong University, China
TH1.R3.2: GRAPH-BASED MICRO-SEISMIC SIGNAL CLASSIFICATION WITH AN OPTIMISED FEATURE SPACE
Jiangfeng Li, University of Strathclyde, United Kingdom; Cheng Yang, York University, Canada; Vladimir Stankovic, Lina Stankovic, Stella Pytharouli, University of Strathclyde, United Kingdom
TH1.R3.3: FEEDBACK NEURAL NETWORK BASED SUPER-RESOLUTION OF DEM FOR GENERATING HIGH FIDELITY FEATURES
Ashish Kubade, Avinash Sharma, K. S. Rajan, International Institute of Information Technology Hyderabad, India
TH1.R3.4: MANIFOLD LEARNING WITH HIGH DIMENSIONAL MODEL REPRESENTATIONS
Gülşen Taşkın, İstanbul Technical University, Turkey; Gustau Camps-Valls, Universitat de Vale ́ncia, Spain
TH1.R3.5: A TENSOR DECOMPOSITION METHOD FOR UNSUPERVISED FEATURE LEARNING ON SATELLITE IMAGERY
Golnoosh Dehghanpoor, Michael Frachetti, Brendan Juba, Washington University in St. Louis, United States
TH1.R3.6: SELF-SUPERVISED REMOTE SENSING IMAGE RETRIEVAL
Kane Walter, Matthew Gibson, Arcot Sowmya, University of New South Wales, Australia
TH1.R3.7: Band-Wise Multi-Scale CNN Architecture for Remote Sensing Image Scene Classification
Jian Kang, Begüm Demir, Technische Universität Berlin, Germany
TH1.R3.8: MULTIFRACTAL FEATURES FOR LAND USE CLASSIFICATION
Anna Wawrzaszek, Centrum Badań Kosmicznych Polskiej Akademii Nauk, Poland; Wojciech Drzewiecki, AGH University of Science and Technology, Poland; Michał Krupiński, Małgorzata Jenerowicz, Sebastian Aleksandrowicz, Centrum Badań Kosmicznych Polskiej Akademii Nauk, Poland
TH1.R3.9: EXTRACTING VEHICLES IN POINT CLOUDS OF UNDERGROUND PARKING LOTS BASED ON GRAPH CONVOLUTION
Di Liu, Zhipeng Luo, Zhenlong Xiao, Xiamen University, China; Jonathan Li, Xiamen University; University of Waterloo, China
TH1.R3.10: A HYBRID MODEL BASED ON FUSED FEATURES FOR DETECTION OF NATURAL DISASTERS FROM SATELLITE IMAGES
Tanu Gupta, Sudip Roy, Indian Institute of Technology Roorkee, India
TH1.R3.11: SYMMETRIC SCATTERING MODEL BASED FEATURE EXTRACTION FROM GENERAL COMPACT POLARIMETRIC SAR IMAGERY
Junjun Yin, University of Science and Technology Beijing, China; Jian Yang, Tsinghua University, China
TH1.R3.12: CNN-based building footprint detection from Sentinel-1 SAR imagery
Andrea Rapuzzi, A-SIGN, Italy; Cristiano Nattero, FadeOut Software srl, Italy; Ramona Pelich, Marco Chini, Luxembourg Institute of Science and Technology (LIST), Luxembourg; Paolo Campanella, FadeOut Software srl, Italy