FR2.W1: Techniques for Classification of Hyperspectral Images II

Session Type: Oral
Time: Friday, July 31, 10:30 - 12:10
Location: White 1
Session Chairs: Mauro Dalla Mura, Gipsa-lab Grenoble-INP and Bing Zhang, RADI
 
FR2.W1.1: TO BE OR NOT TO BE CONVEX? A STUDY ON REGULARIZATION IN HYPERSPECTRAL IMAGE CLASSIFICATION
         Devis Tuia; University of Zurich
         Remi Flamary; Universit√© de Nice Sophia Antipolis
         Michel Barlaud; Universit√© de Nice Sophia Antipolis
 
FR2.W1.2: DEEP FEATURE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Jiming Li; Zhejiang Police College
         Lorenzo Bruzzone; University of Trento
         Sicong Liu; University of Trento
 
FR2.W1.3: ADAPTIVE SPARSE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Wei Li; Beijing University of Chemical Technology
         Qian Du; Mississippi State University
 
FR2.W1.4: DEEP SUPERVISED LEARNING FOR HYPERSPECTRAL DATA CLASSIFICATION THROUGH CONVOLUTIONAL NEURAL NETWORKS
         Konstantinos Makantasis; Technical University of Crete
         Konstantinos Karantzalos; National Technical University of Athens
         Anastasios Doulamis; National Technical University of Athens
         Nikolaos Doulamis; National Technical University of Athens
 
FR2.W1.5: AN ENSEMBLE ACTIVE LEARNING APPROACH FOR SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES
         Zhou Zhang; Purdue University
         Melba M. Crawford; Purdue University