TU2.R5.3

HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON MULTISCALE SPATIAL AND SPECTRAL FEATURE NETWORK

Xu Tang, Fanbo Meng, Jingjing Ma, Xiangrong Zhang, Xidian University, China; Fang Liu, Nanjing University of Science and Technology, China; Qunnie Peng, Science and Technology on Electro-optic Control Laboratory, China; Licheng Jiao, Xidian University, China

Session:
Hyperspectral Image Classification II

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Tue, 29 Sep, 14:50-15:00 (UTC)
Tue, 29 Sep, 22:50-23:00 China Standard Time (UTC +8)
Tue, 29 Sep, 16:50-17:00 Central Europe Summer Time (UTC +2)
Tue, 29 Sep, 07:50-08:00 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Licheng Jiao, Xidian University and Qian Du, Mississippi State University
Session Managers:
Subhadip Dey and Shivam Pande

Presentation

Discussion

Resources

Session

TU2.R5.1: Two-step ensemble based class noise cleaning method for hyperspectral image classification
Wei Feng, Yinghui Quan, School of Electronic Engineering, Xidian University, China; Gabriel Dauphin, Institut Galilée, University Paris XIII, France; Xian Zhong, School of Electronic Engineering, Xidian University, China; Qiang Li, Northwestern Polytechnical University, China; Mengdao Xing, Xidian University, China; Wenjiang Huang, Chinese Academy of Sciences, China
TU2.R5.2: A SUPERPIXEL-BASED FRAMEWORK FOR NOISY HYPERSPECTRAL IMAGE CLASSIFICATION
Peng Fu, Quansen Sun, Zexuan Ji, Nanjing University of Science and Technology, China; Leilei Geng, Shandong University of Finance and Economics, China
TU2.R5.3: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON MULTISCALE SPATIAL AND SPECTRAL FEATURE NETWORK
Xu Tang, Fanbo Meng, Jingjing Ma, Xiangrong Zhang, Xidian University, China; Fang Liu, Nanjing University of Science and Technology, China; Qunnie Peng, Science and Technology on Electro-optic Control Laboratory, China; Licheng Jiao, Xidian University, China
TU2.R5.4: IMPROVING HYPERSPECTRAL IMAGE CLASSIFICATION USING GRAPH WAVELETS
Qipeng Qian, Shanghai Jiao Tong University, China; Xiaotian Fan, Zhejiang University, China; Minchao Ye, China Jiliang Universit, China
TU2.R5.5: JOINT GROUP SPARSE COLLABORATIVE REPRESENTATION FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Qing Tian, Juan Zhao, Xia Bai, Beijing Institute of Technology, China
TU2.R5.6: PERONA-MALIK DIFFUSION DRIVEN CNN FOR SUPERVISED CLASSIFICATION OF HYPERSPECTRAL IMAGES
Ning Wen, Qichao Liu, Liang Xiao, Nanjing University of Science and Technology, China
TU2.R5.7: A DIRECTIONAL MESSAGE PROPAGATION CONVOLUTIONAL NEURAL NETWORK FOR HYPERSPECTRAL IMAGES CLASSIFICATION
Jian Yu, Qichao Liu, Liang Xiao, Zhihui Wei, Nanjing University of Science and Technology, China
TU2.R5.8: Hyperspectral Image Classification Based on Tensor-Train Convolutional Long Short-Term Memory
Wenshuai Hu, Hengchao Li, Tianyu Ma, Southwest Jiaotong University, China; Qian Du, Mississippi State University, United States; Antonio Plaza, University of Extremadura, Spain; William J. Emery, University of Colorado, United States
TU2.R5.9: ADAPTIVE NEIGHBORHOOD STRATEGY BASED GENERATIVE ADVERSARIAL NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Hongbo Liang, Wenxing Bao, Bingbing Lei, Jian Zhang, Kewen Qu, School of Computer Science and Engineering, North Minzu University, China
TU2.R5.10: HYPERSPECTRAL IMAGE CLASSIFICATION USING SPECTRAL-SPATIAL CONVOLUTIONAL NEURAL NETWORKS
Jakub Nalepa, Lukasz Tulczyjew, Michal Myller, Michal Kawulok, KP Labs, Silesian University of Technology, Poland
TU2.R5.11: SEGMENTING HYPERSPECTRAL IMAGES USING SPECTRAL CONVOLUTIONAL NEURAL NETWORKS IN THE PRESENCE OF NOISE
Jakub Nalepa, Silesian University of Technology, KP Labs, Poland; Marek Stanek, Silesian University of Technology, Poland