WE4.R1: Learning and Domain Adaptation

Session Type: Oral
Time: Wednesday, July 25, 16:50 - 18:30
Location: Room 1D
Session Chair: Shutao Li, Hunan University
 
16:50 - 17:10
WE4.R1.1: SEMISUPERVISED ADVERSARIAL DISCRIMINATIVE DOMAIN ADAPTATION, WITH APPLICATION TO REMOTE SENSING DATA
         Rui Wang; Duke University
         Leslie Collins; Duke University
         Kyle Bradbury; Duke University
         Jordan Malof; Duke University
 
17:10 - 17:30
WE4.R1.2: BOOSTING FOR DOMAIN ADAPTATION EXTREME LEARNING MACHINES FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Junshi Xia; The University of Tokyo
         Naoto Yokoya; RIKEN Center for Advanced Intelligence Project
         Akira Iwasaki; The University of Tokyo
 
17:30 - 17:50
WE4.R1.3: A NOVEL METHOD BASED ON SOURCE DOMAIN UNDERSTANDING AND MODELING TO TRANSFER LABELS FROM LAND-COVER VECTOR MAPS TO CLASSIFIERS FOR MULTISPECTRAL IMAGES
         Claudia Paris; University of Trento
         Lorenzo Bruzzone; University of Trento
         Diego Fernández-Prieto; European Space Agency
 
17:50 - 18:10
WE4.R1.4: DOMAIN ADAPTATION FOR LARGE SCALE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE IMAGES WITH DEEP CONVOLUTIONAL NEURAL NETWORKS
         Tristan Postadjian; Univ. Paris Est, LASTIG MATIS, IGN, ENSG
         Arnaud Le Bris; Univ. Paris Est, LASTIG MATIS, IGN, ENSG
         Hichem Sahbi; CNRS, LIP6 UPMC Sorbonne Universités, Paris
         Clément Mallet; Univ. Paris Est, LASTIG MATIS, IGN, ENSG
 
18:10 - 18:30
WE4.R1.5: CROSS-DOMAIN CNN FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Hyungtae Lee; Booz Allen Hamilton Inc.
         Sungmin Eum; Booz Allen Hamilton Inc.
         Heesung Kwon; US Army Research Laboratory