TP-L.C2: Learning for Segmentation
Tue, 18 Oct, 22:30 - 00:30 China Standard Time (UTC +8)
Tue, 18 Oct, 16:30 - 18:30 Central European Time (UTC +1)
Tue, 18 Oct, 14:30 - 16:30 UTC
Tue, 18 Oct, 10:30 - 12:30 Eastern Time (UTC -5)
Lecture
Location: Room C2
Session Chair: Christophe de Vleeschouwer, UCL
Track: Applications of Machine Learning

TP-L.C2.1: REVERSE ERROR MODELING FOR IMPROVED SEMANTIC SEGMENTATION
Christopher Kuhn, Technical University of Munich and CareX, Germany; Markus Hofbauer, Eckehard Steinbach, Technical University of Munich, Germany; Goran Petrovic, BMW Group, Germany

TP-L.C2.2: ENTROPY-BASED FEATURE EXTRACTION FOR REAL-TIME SEMANTIC SEGMENTATION
Lusine Abrahamyan, Nikos Deligiannis, Vrije Universiteit Brussel, Belgium

TP-L.C2.3: FULLY CONVOLUTIONAL AND FEEDFORWARD NETWORKS FOR THE SEMANTIC SEGMENTATION OF REMOTELY SENSED IMAGES
Martina Pastorino, Università di Genova, INRIA d'Université Côte d'Azur, Italy; Gabriele Moser, Sebastiano B. Serpico, Università di Genova, Italy; Josiane Zerubia, INRIA d'Université Côte d'Azur, France

TP-L.C2.4: REAL- AND COMPLEX-VALUED NEURAL NETWORKS FOR SAR IMAGE SEGMENTATION THROUGH DIFFERENT POLARIMETRIC REPRESENTATIONS
Jose Agustin Barrachina, Jean-Philippe Ovarlez, ONERA / CentraleSupelec, France; Chengfang Ren, CentraleSupelec, France; Gilles Vieillard, Christele Morisseau, ONERA, France

TP-L.C2.5: IS THE U-NET DIRECTIONAL-RELATIONSHIP AWARE?
Mateus Riva, Pietro Gori, Télécom Paris, France; Florian Yger, Université Paris-Dauphine, France; Isabelle Bloch, Sorbonne Université, France