MO4.R4.5

SUPERVISED MULTI-TASK LEARNING FOR TRACKING INLAND GLACIER FLOWS USING SENTINEL-1 TOPS DATA

Andrea Pulella, German Aerospace Center (DLR), Germany; Francescopaolo Sica, University of the Bundeswehr Munich, Germany; Pau Prats-Iraola, German Aerospace Center (DLR), Germany
Session:
MO4.R4: Give Earth a Chance: Artificial Intelligence Meets Remote Sensing for Environmental Monitoring I Oral
Track:
Community-Contributed Sessions
Location:
Conference Hall 1
Presentation Time:
Mon, 8 Jul, 17:16 - 17:30
Session Co-Chairs:
Agata M. Wijata, KP Labs / Silesian University of Technology and Jakub Nalepa, KP Labs / Silesian University of Technology
Presentation
Discussion
Resources
No resources available.
Session MO4.R4
MO4.R4.1: MOUNTAIN GREEN COVER INDEX CALCULATION AT A NATIONAL SCALE USING WEAK AND SPARSE DATA
Natalia Verde, Petros Patias, Giorgos Mallinis, Aristotle University, Greece
MO4.R4.2: MULTI-SCALE CONTEXT FUSION FOR PIXEL-LEVEL NATURALNESS MAPPING USING SENTINEL-2 IMAGERY
Burak Ekim, Michael Schmitt, University of the Bundeswehr Munich, Germany
MO4.R4.3: SOIL ANALYSIS WITH VERY FEW LABELS USING SEMI-SUPERVISED HYPERSPECTRAL IMAGE CLASSIFICATION
Bartosz Grabowski, KP Labs, Poland; Agata M. Wijata, Lukasz Tulczyjew, KP Labs / Silesian University of Technology, Poland; Bertrand Le Saux, European Space Agency, Italy; Jakub Nalepa, KP Labs / Silesian University of Technology, Poland
MO4.R4.4: ESTIMATING SOIL PARAMETERS FROM HYPERSPECTRAL IMAGES USING ENSEMBLES OF CLASSIC AND DEEP MACHINE LEARNING MODELS
Wiktor Gacek, Silesian University of Technology, Poland; Lukasz Tulczyjew, Agata M. Wijata, KP Labs / Silesian University of Technology, Poland; Nicolas Longépé, Bertrand Le Saux, European Space Agency, Italy; Jakub Nalepa, KP Labs / Silesian University of Technology, Poland
MO4.R4.5: SUPERVISED MULTI-TASK LEARNING FOR TRACKING INLAND GLACIER FLOWS USING SENTINEL-1 TOPS DATA
Andrea Pulella, German Aerospace Center (DLR), Germany; Francescopaolo Sica, University of the Bundeswehr Munich, Germany; Pau Prats-Iraola, German Aerospace Center (DLR), Germany
MO4.R4.6: DEEP LEARNING FOR CROSS-DOMAIN BUILDING CHANGE DETECTION FROM MULTI-SOURCE VERY HIGH-RESOLUTION SATELLITE IMAGERY
Getachew Workineh Gella, Stefan Lang, Paris Lodron University of Salzburg(PLUS), Austria
MO4.R4.7: QUANTIFYING HETEROGENEOUS ECOSYSTEM SERVICES WITH MULTI-LABEL SOFT CLASSIFICATION
Zhihui Tian, John Upchurch, Geoffrey Simon, Jose Dubeux, Alina Zare, university of florida, United States; Chang Zhao, University of Florida, United States; Joel Harley, university of florida, United States
Resources
No resources available.