MO4.L3: Ship Detection

Session Type: Oral
Time: Monday, July 11, 15:40 - 17:20
Location: Room 308
Session Chair: Xiaofeng Li, NOAA/NESDIS
 
15:40 - 16:00
MO4.L3.1: ATTRIBUTE LEARNING FOR SHIP CATEGORY RECOGNITION IN REMOTE SENSING IMAGERY
         Quentin Oliveau; Télécom ParisTech
         Hichem Sahbi; Télécom ParisTech
 
16:00 - 16:20
MO4.L3.2: A NOVEL THRESHOLD TEMPLATE ALGORITHM FOR SHIP DETECTION IN HIGH-RESOLUTION SAR IMAGES
         Chonglei Wang; Beijing Institute of Technology
         Fukun Bi; North China University of Technology
         Liang Chen; Beijing Institute of Technology
         Jing Chen; North China University of Technology
 
16:20 - 16:40
MO4.L3.3: VERY DEEP LEARNING FOR SHIP DISCRIMINATION IN SYNTHETIC APERTURE RADAR IMAGERY
         Colin Peter Schwegmann; Council for Scientific and Industrial Research
         Waldo Kleynhans; Council for Scientific and Industrial Research
         Brian Salmon; University of Tasmania
         Lizwe Mdakane; Council for Scientific and Industrial Research
         Rory Meyer; Council for Scientific and Industrial Research
 
16:40 - 17:00
MO4.L3.4: A NOVEL ADAPTIVE SHIP DETECTION METHOD FOR SPACEBORNE SAR IMAGERY
         Xiangguang Leng; National University of Defense Technology
         Kefeng Ji; National University of Defense Technology
         Qingju Fan; National University of Defense Technology
         Shilin Zhou; National University of Defense Technology
         Huanxin Zou; National University of Defense Technology
 
17:00 - 17:20
MO4.L3.5: A NEW POLSAR SHIP DETECTION METRIC FUSED BY POLARIMETRIC SIMILARITY AND THE THIRD EIGENVALUE OF THE COHERENCY MATRIX
         Yuyang Xi; Beijing University of Chemical Technology
         Xi Zhang; State Oceanic Administration
         Quan Lai; Inner Mongolia Normal University
         Wei Li; Beijing University of Chemical Technology
         Haitao Lang; Beijing University of Chemical Technology