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My IGARSS 2016 Schedule

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MOP.P4: Classification of Hyperspectral Image II

Session Type: Poster
Time: Monday, July 11, 17:20 - 19:00
Location: Third Floor, South Hall, Poster Area
Session Chair: Peijun Li, University of Peking
 
  MOP.P4.21: LOCALITY CONSTRAINED LOW-RANK REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Lei Pan; Southwest Jiaotong University
         Heng-Chao Li; Southwest Jiaotong University
         Xiang-Dong Chen; Southwest Jiaotong University
 
  MOP.P4.22: ELM-BASED SPECTRAL–SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES USING BILATERAL FILTERING INFORMATION ON SPECTRAL BAND-SUBSETS
         Yu Shen; Nanjing University of Science and Technology
         Jinhuan Xu; Nanjing University of Science and Technology
         Heng Li; Nanjing University of Science and Technology
         Liang Xiao; Nanjing University of Science and Technology
 
  MOP.P4.23: SPATIALLY CONSTRAINED BAG-OF-VISUAL-WORDS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Xiangrong Zhang; Xidian University
         Kai Jiang; Xidian University
         Yaoguo Zheng; Xidian University
         Jinliang An; Xidian University
         Yanning Hu; Xidian University
         Licheng Jiao; Xidian University
 
  MOP.P4.24: MULTI-CLASSIFICATION METHOD FOR HYPERSPECTRAL DATA BASED ON CHERNOFF DISTANCE AND PAIRWISE DECISION TREE STRATEGY
         Miao Zhang; Harbin Institute of Technology
         Zheqi Lin; Harbin Institute of Technology
         Yiming Cui; Harbin Institute of Technology
         Fei Shen; Shanghai Institute of Spaceflight Control Technology
         Yi Shen; Harbin Institute of Technology
 
  MOP.P4.25: NON-LOCAL SPECTRAL-SPATIAL CENTRALIZED SPARSE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Bushra Naz Soomro; Nanjing University of Science and Technology
         Liang Xiao; Nanjing University of Science and Technology
         Shahzad Hyder Soomro; Nanjing University of Science and Technology
 
  MOP.P4.26: MAPPING LAND COVER WITH HYPERSPECTRAL AND MULTISPECTRAL SATELLITES USING MACHINE LEARNING AND SPECTRAL MIXTURE ANALYSIS
         Matthew Clark; Sonoma State University