FR4.L1: Deep Learning using Hyperspectral and SAR Imagery |
Session Type: Oral |
Time: Friday, July 28, 15:50 - 17:30 |
Location: Ballroom B |
Session Chairs: Emmanuel Maggiori, Inria Sophia Antipolis-Méditerranée and Yuliya Tarabalka, Inria Sophia Antipolis-Méditerranée |
15:50 - 16:10 |
FR4.L1.1: TRANSFERRED DEEP LEARNING FOR HYPERSPECTRAL TARGET DETECTION |
Wei Li; Beijing University of Chemical Technology |
Guodong Wu; Beijing University of Chemical Technology |
Qian Du; Mississippi State University |
16:10 - 16:30 |
FR4.L1.2: FULLY CONV-DECONV NETWORK FOR UNSUPERVISED SPECTRAL-SPATIAL FEATURE EXTRACTION OF HYPERSPECTRAL IMAGERY VIA RESIDUAL LEARNING |
Lichao Mou; German Aerospace Center; Technical University of Munich |
Pedram Ghamisi; German Aerospace Center; Technical University of Munich |
Xiao Xiang Zhu; German Aerospace Center; Technical University of Munich |
16:30 - 16:50 |
FR4.L1.3: HYPERSPECTRAL DATA CLASSIFICATION USING CONVOLUTIONAL RECURRENT NEURAL NETWORKS |
Hao Wu; University of Hosuton |
Saurabh Prasad; University of Hosuton |
16:50 - 17:10 |
FR4.L1.4: UNMIXING IN THE PRESENCE OF NUISANCES WITH DEEP GENERATIVE MODELS |
Mario Parente; University of Massachusetts Amherst |
Ian Gemp; University of Massachusetts Amherst |
Ishan Durugkar; University of Massachusetts Amherst |
17:10 - 17:30 |
FR4.L1.5: A NOVEL CHANGE DETECTION FRAMEWORK BASED ON DEEP LEARNING FOR THE ANALYSIS OF MULTI-TEMPORAL POLARIMETRIC SAR IMAGES |
Shaunak De; Indian Institute of Technology Bombay |
Davide Pirrone; Fondazione Bruno Kessler |
Francesca Bovolo; Fondazione Bruno Kessler |
Lorenzo Bruzzone; University of Trento |
Avik Bhattacharya; Indian Institute of Technology Bombay |