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.R4.7: 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