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
Session:
Learning for Segmentation
Lecture
Track:
Applications of Machine Learning
Location:
Room C2
Presentation Time:
Tue, 18 Oct, 23:00 - 23:15 China Standard Time (UTC +8)
Tue, 18 Oct, 17:00 - 17:15 Central European Time (UTC +2)
Tue, 18 Oct, 15:00 - 15:15 UTC
Tue, 18 Oct, 11:00 - 11:15 Eastern Time (UTC -4)
Session Chair:
Christophe de Vleeschouwer, UCL
Presentation
Discussion
Resources
No resources available.
Session TP-L.C2
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