TH1.T09: New Trends in Machine Learning for Remote Sensing

Session Type: Oral
Time: Thursday, July 28, 08:20 - 10:00
Location: Ballroom C
Session Chairs: Melba Crawford, Purdue University and Devis Tuia, University of Lausanne
 
TH1.T09.1: EXPLICIT SIGNAL TO NOISE RATIO IN REPRODUCING KERNEL HILBERT SPACES
         Luis Gómez-Chova; Universitat de València
         Allan A. Nielsen; Technical University of Denmark
         Gustavo Camps-Valls; Technical University of Denmark
 
TH1.T09.2: GAUSSIAN PROCESS REGRESSION WITHIN AN ACTIVE LEARNING SCHEME
         Edoardo Pasolli; University of Trento
         Farid Melgani; University of Trento
 
TH1.T09.3: TEMPORAL DOMAIN ADAPTATION UNDER TIME WARPING
         Francois Petitjean; LSIIT, UMR 7005
         Jordi Inglada; Centre National d'Etudes Spatiales (CNES)
         Pierre Gancarski; LSIIT, UMR 7005 - University of Strasbourg
 
TH1.T09.4: CONJUNCTIVE FORMULATION OF THE RANDOM SET FRAMEWORK FOR MULTIPLE INSTANCE LEARNING: APPLICATION TO REMOTE SENSING
         Jeremy Bolton; University of Florida
         Paul Gader; University of Florida
 
TH1.T09.5: HYPERSPECTRAL UNMIXING WITH SPARSE GROUP LASSO
         Marian-Daniel Iordache; Hyperspectral Computing Laboratory
         Jose Bioucas-Dias; Instituto de Telecomunicacoes
         Antonio Plaza; Hyperspectral Computing Laboratory