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Session Detail

Session Title TU2.R5: Hyperspectral Image Classification II
Presentation Mode Virtual
Session Time Tue, 29 Sep, 14:30 - 16:30 UTC
Tue, 29 Sep, 22:30 - 00:30 China Standard Time (UTC +8)
Tue, 29 Sep, 16:30 - 18:30 Central Europe Time (UTC +2)
Tue, 29 Sep, 07:30 - 09:30 Pacific Daylight Time (UTC -7)
Session ChairsLicheng Jiao, Xidian University and Qian Du, Mississippi State University

TU2.R5.1: TWO-STEP ENSEMBLE BASED CLASS NOISE CLEANING METHOD FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Wei Feng; School of Electronic Engineering, Xidian University
         Yinghui Quan; School of Electronic Engineering, Xidian University
         Gabriel Dauphin; Institut Galilée, University Paris XIII
         Xian Zhong; School of Electronic Engineering, Xidian University
         Qiang Li; Northwestern Polytechnical University
         Mengdao Xing; Xidian University
         Wenjiang Huang; Chinese Academy of Sciences

TU2.R5.2: A SUPERPIXEL-BASED FRAMEWORK FOR NOISY HYPERSPECTRAL IMAGE CLASSIFICATION
         Peng Fu; Nanjing University of Science and Technology
         Quansen Sun; Nanjing University of Science and Technology
         Zexuan Ji; Nanjing University of Science and Technology
         Leilei Geng; Shandong University of Finance and Economics

TU2.R5.3: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON MULTISCALE SPATIAL AND SPECTRAL FEATURE NETWORK
         Xu Tang; Xidian University
         Fanbo Meng; Xidian University
         Jingjing Ma; Xidian University
         Xiangrong Zhang; Xidian University
         Fang Liu; Nanjing University of Science and Technology
         Qunnie Peng; Science and Technology on Electro-optic Control Laboratory
         Licheng Jiao; Xidian University

TU2.R5.4: IMPROVING HYPERSPECTRAL IMAGE CLASSIFICATION USING GRAPH WAVELETS
         Qipeng Qian; Shanghai Jiao Tong University
         Xiaotian Fan; Zhejiang University
         Minchao Ye; China Jiliang Universit

TU2.R5.5: JOINT GROUP SPARSE COLLABORATIVE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Qing Tian; Beijing Institute of Technology
         Juan Zhao; Beijing Institute of Technology
         Xia Bai; Beijing Institute of Technology

TU2.R5.6: PERONA-MALIK DIFFUSION DRIVEN CNN FOR SUPERVISED CLASSIFICATION OF HYPERSPECTRAL IMAGES
         Ning Wen; Nanjing University of Science and Technology
         Qichao Liu; Nanjing University of Science and Technology
         Liang Xiao; Nanjing University of Science and Technology

TU2.R5.7: A DIRECTIONAL MESSAGE PROPAGATION CONVOLUTIONAL NEURAL NETWORK FOR HYPERSPECTRAL IMAGES CLASSIFICATION
         Jian Yu; Nanjing University of Science and Technology
         Qichao Liu; Nanjing University of Science and Technology
         Liang Xiao; Nanjing University of Science and Technology
         Zhihui Wei; Nanjing University of Science and Technology

TU2.R5.8: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON TENSOR-TRAIN CONVOLUTIONAL LONG SHORT-TERM MEMORY
         Wenshuai Hu; Southwest Jiaotong University
         Hengchao Li; Southwest Jiaotong University
         Tianyu Ma; Southwest Jiaotong University
         Qian Du; Mississippi State University
         Antonio Plaza; University of Extremadura
         William J. Emery; University of Colorado

TU2.R5.9: ADAPTIVE NEIGHBORHOOD STRATEGY BASED GENERATIVE ADVERSARIAL NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
         Hongbo Liang; School of Computer Science and Engineering, North Minzu University
         Wenxing Bao; School of Computer Science and Engineering, North Minzu University
         Bingbing Lei; School of Computer Science and Engineering, North Minzu University
         Jian Zhang; School of Computer Science and Engineering, North Minzu University
         Kewen Qu; School of Computer Science and Engineering, North Minzu University

TU2.R5.10: HYPERSPECTRAL IMAGE CLASSIFICATION USING SPECTRAL-SPATIAL CONVOLUTIONAL NEURAL NETWORKS
         Jakub Nalepa; KP Labs, Silesian University of Technology
         Lukasz Tulczyjew; KP Labs, Silesian University of Technology
         Michal Myller; KP Labs, Silesian University of Technology
         Michal Kawulok; KP Labs, Silesian University of Technology

TU2.R5.11: SEGMENTING HYPERSPECTRAL IMAGES USING SPECTRAL CONVOLUTIONAL NEURAL NETWORKS IN THE PRESENCE OF NOISE
         Jakub Nalepa; Silesian University of Technology, KP Labs
         Marek Stanek; Silesian University of Technology