MOP2.PT: Big Machine Learning II

Session Type: Poster
Time: Monday, July 23, 15:50 - 16:50
Location: Poster Area T
Session Chair: Francesca Bovolo, Fondazione Bruno Kessler
 
MOP2.PT.1: DEEP LEARNING – A NEW APPROACH FOR MULTI-LABEL SCENE CLASSIFICATION IN PLANETSCOPE AND SENTINEL-2 IMAGERY
         Iurii Shendryk; The Commonwealth Scientific and Industrial Research Organisation
         Yannik Rist; The Commonwealth Scientific and Industrial Research Organisation
         Rob Lucas; The Commonwealth Scientific and Industrial Research Organisation
         Catherine Ticehurst; The Commonwealth Scientific and Industrial Research Organisation
         Peter Thorburn; The Commonwealth Scientific and Industrial Research Organisation
 
MOP2.PT.2: PATTERN STRENGTHENED DEEP MODEL FOR SAR IMAGE CLASSIFICATION
         Xinlong Liu; Electronic Information School, Wuhan University
         Yan Wang; Electronic Information School, Wuhan University
         Gong Han; Electronic Information School, Wuhan University
         Mingxia Tu; Wuhan University
         Chu He; Electronic Information School, Wuhan University
 
MOP2.PT.3: DEEP SEMANTIC HASHING RETRIEVAL OF REMOTE SENSING IMAGES
         Cheng Chen; National University of Defense Technology
         Huanxin Zou; National University of Defense Technology
         Ningyuan Shao; National University of Defense Technology
         Jiachi Sun; National University of Defense Technology
         Xianxiang Qin; Air Force Engineering University
 
MOP2.PT.4: AUTOMATED ANALYSIS OF REMOTELY SENSED IMAGES USING THE UNICORE WORKFLOW MANAGEMENT SYSTEM
         Shahbaz Memon; Forschungszentrum Jülich
         Gabriele Cavallaro; Forschungszentrum Jülich
         Björn Hagemeier; Forschungszentrum Jülich
         Morris Riedel; Forschungszentrum Jülich
         Helmut Neukirchen; University of Iceland
 
MOP2.PT.5: POTENTIAL ANALYSIS OF FEATURE EXTRACTION BASED QUICK RESPONSE FOR ENVIRONMENTAL CHANGE WITH SOCIAL MEDIA PHOTOS
         Yuanfeng Wu; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
         Lianru Gao; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
         Wenzhi Liao; Ghent University-TELIN-IPI-IMEC, Belgium
         Paolo Gamba; Dipartimento di Ingegneria Industriale e dell’Informazione, Università degli Studi di Pavia
         Bing Zhang; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
 
MOP2.PT.6: TIME-SCALE TRANSFERRING DEEP CONVOLUTIONAL NEURAL NETWORK FOR MAPPING EARLY RICE
         Yaming Duan; College of Resources Science and Technology/Skate Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University
         Jinshui Zhang; College of Resources Science and Technology/Skate Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University
         Guanyuan Shuai; Department of Earth and Environment Science, Michigan State University
         Shuang Zhu; Beijing Polytechnic College, Beijing 100042, China
         Xiaohe Gu; Beijing Polytechnic College / ChinaBeijing Polytechnic College
 
MOP2.PT.7: AUTOMATIC ROAD EXTRACTION IN HIGH RESOLUTION REMOTE SENSING IMAGES VIA GENERATIVE ADVERSARIAL NETWORKS
         Yuming Xiang; Institute of Electronics, Chinese Academy of Sciences
         Feng Wang; Institute of Electronics, Chinese Academy of Sciences
         Wenchao Kang; Institute of Electronics, Chinese Academy of Sciences
         Hongjian You; Institute of Electronics, Chinese Academy of Sciences
 
MOP2.PT.8: COMBINING FOURIER ANALYSIS AND MACHINE LEARNING TO ESTIMATE THE SHALLOW-GROUND THERMAL DIFFUSIVITY IN SWITZERLAND
         Dan Assouline; Ecole Polytechnique Federale de Lausanne (EPFL)
         Nahid Mohajeri; University of Oxford
         Agust Gudmundsson; Royal Holloway University of London
         Jean-Louis Scartezzini; Ecole Polytechnique Federale de Lausanne (EPFL)
 
MOP2.PT.9: SUPER-RESOLUTION OF REMOTE SENSING IMAGES BASED ON TRANSFERRED GENERATIVE ADVERSARIAL NETWORK
         Wen Ma; University of Chinese Academy of Sciences; Institute of Electronics, Chinese Academy of Sciences; Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences
         Zongxu Pan; Institute of Electronics, Chinese Academy of Sciences; Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences
         Jiayi Guo; University of Chinese Academy of Sciences; Institute of Electronics, Chinese Academy of Sciences; Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences
         Bin Lei; Institute of Electronics, Chinese Academy of Sciences; Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences