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TU2.R5.1: TWO-STEP ENSEMBLE BASED CLASS NOISE CLEANING METHOD FOR HYPERSPECTRAL IMAGE CLASSIFICATION
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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 |
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TU2.R5.2: A SUPERPIXEL-BASED FRAMEWORK FOR NOISY HYPERSPECTRAL IMAGE CLASSIFICATION
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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 |
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TU2.R5.3: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON MULTISCALE SPATIAL AND SPECTRAL FEATURE NETWORK
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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 |
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TU2.R5.4: IMPROVING HYPERSPECTRAL IMAGE CLASSIFICATION USING GRAPH WAVELETS
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Qipeng Qian; Shanghai Jiao Tong University |
Xiaotian Fan; Zhejiang University |
Minchao Ye; China Jiliang Universit |
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TU2.R5.5: JOINT GROUP SPARSE COLLABORATIVE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
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Qing Tian; Beijing Institute of Technology |
Juan Zhao; Beijing Institute of Technology |
Xia Bai; Beijing Institute of Technology |
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TU2.R5.6: PERONA-MALIK DIFFUSION DRIVEN CNN FOR SUPERVISED CLASSIFICATION OF HYPERSPECTRAL IMAGES
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Ning Wen; Nanjing University of Science and Technology |
Qichao Liu; Nanjing University of Science and Technology |
Liang Xiao; Nanjing University of Science and Technology |
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TU2.R5.7: A DIRECTIONAL MESSAGE PROPAGATION CONVOLUTIONAL NEURAL NETWORK FOR HYPERSPECTRAL IMAGES CLASSIFICATION
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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 |
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TU2.R5.8: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON TENSOR-TRAIN CONVOLUTIONAL LONG SHORT-TERM MEMORY
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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 |
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TU2.R5.9: ADAPTIVE NEIGHBORHOOD STRATEGY BASED GENERATIVE ADVERSARIAL NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
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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 |
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TU2.R5.10: HYPERSPECTRAL IMAGE CLASSIFICATION USING SPECTRAL-SPATIAL CONVOLUTIONAL NEURAL NETWORKS
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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 |
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TU2.R5.11: SEGMENTING HYPERSPECTRAL IMAGES USING SPECTRAL CONVOLUTIONAL NEURAL NETWORKS IN THE PRESENCE OF NOISE
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Jakub Nalepa; Silesian University of Technology, KP Labs |
Marek Stanek; Silesian University of Technology |