Technical Program

Session Detail

Session Title WE2.R5: Analysis of Time Series
Presentation Mode Oral
Session Time Wednesday, 31 July, 10:40 - 12:20
Location Room 315
Session ChairsLorenzo Bruzzone, University of Trento and Qian Du, Mississippi State University

WE2.R5.1: A SEMI-SUPERVISED CROP-TYPE CLASSIFICATION BASED ON SENTINEL-2 NDVI SATELLITE IMAGE TIME SERIES AND PHENOLOGICAL PARAMETERS
         Yady Tatiana Solano-Correa; Fondazione Bruno Kessler
         Francesca Bovolo; Fondazione Bruno Kessler
         Lorenzo Bruzzone; University of Trento

WE2.R5.2: DEEP LEARNING FOR THE CLASSIFICATION OF SENTINEL-2 IMAGE TIME SERIES
         Charlotte Pelletier; Monash University
         Geoffrey I Webb; Monash University
         François Petitjean; Monash University

WE2.R5.3: IMPROVING HYPERSPECTRAL IMAGE CLASSIFICATION BY COMBINING SPECTRAL AND MULTIBAND COMPACT TEXTURE FEATURES
         Khelifa Djerriri; Centre des Techniques Spatiales
         Abdelmounaime Safia; Centre d’applications et de Recherches en Télédétection (CARTEL)
         Reda Adjoudj; Djillali Liabes University
         Moussa Sofiane Karoui; Centre des Techniques Spatiales

WE2.R5.4: COMPARING PHENOMETRICS EXTRACTED FROM DENSE LANDSAT-LIKE IMAGE TIME SERIES FOR CROP CLASSIFICATION
         Hugo Bendini; National Institute for Space Research (INPE)
         Leila Fonseca; National Institute for Space Research (INPE)
         Marcel Schwieder; Humboldt-Universität zu Berlin
         Thales Körting; National Institute for Space Research (INPE)
         Philippe Rufin; Humboldt-Universität zu Berlin
         Ieda Sanches; National Institute for Space Research (INPE)
         Pedro Leitão; Humboldt-Universität zu Berlin
         Patrick Hostert; Humboldt-Universität zu Berlin

WE2.R5.5: DEEP RECURRENT NEURAL NETWORKS FOR LAND-COVER CLASSIFICATION USING SENTINEL-1 INSAR TIME SERIES
         Shaojia Ge; Nanjing University of Science and Technology
         Oleg Antropov; VTT Technical Research Centre of Finland
         Weimin Su; Nanjing University of Science and Technology
         Hong Gu; Nanjing University of Science and Technology
         Jaan Praks; Aalto University