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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU2.MM-8.3

COLLABORATIVE AND LOW-RANK GRAPH FOR DISCRIMINANT ANALYSIS OF HYPERSPECTRAL IMAGERY

Chiranjibi Shah, Qian Du, Mississippi State University, United States
Session:
Hyperspectral Image Classification
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Tue, 13 Jul, 11:10-11:15 (UTC)
Tue, 13 Jul, 13:10-13:15 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 19:10-19:15 China Standard Time (UTC +8)
Tue, 13 Jul, 07:10-07:15 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Qian Du, Mississippi State University and Dandan Ma, Northwestern Polytechnical University
Session Manager:
Anna Mateo-Sanchis
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Session TU2.MM-8
TU2.MM-8.1: A Binary Feature Representation Method for Hyperspectral Image Classification
Changda Xing, Meiling Wang, Zhisheng Wang, Chaowei Duan, Yiliu Liu, Nanjing University of Aeronautics and Astronautics, China
TU2.MM-8.2: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON EXTENDED MORPHOLOGICAL PROFILE FEATURES AND GHOST MODULE
Size Liu, Bixiu Ding, Jing Bai, Xidian University, China; Zhu Xiao, Hunan University, China
TU2.MM-8.3: COLLABORATIVE AND LOW-RANK GRAPH FOR DISCRIMINANT ANALYSIS OF HYPERSPECTRAL IMAGERY
Chiranjibi Shah, Qian Du, Mississippi State University, United States
TU2.MM-8.4: Group-Aware Low-Rank Representation for Hyperspectral Image Classification
Changda Xing, Meiling Wang, Zhisheng Wang, Chaowei Duan, Yiliu Liu, Nanjing University of Aeronautics and Astronautics, China
TU2.MM-8.5: ADAPTIVE SPECTRAL AND SPATIAL FEATURE EXTRACTION FRAMEWORK FOR HYPERSPECTRAL CLASSIFICATION
Wenchao Wang, Yuan Yuan, Dandan Ma, Northwestern Polytechnical University, China
TU2.MM-8.6: KEROGEN TYPE CLASSIFICATION IN HYDROCARBON SOURCE ROCKS USING HYPERSPECTRAL DATA AND MACHINE LEARNING
Tainá Thomassim Guimarães, Lucas Silveira Kupssinskü, Daniel Capella Zanotta, João Gabriel Motta, Unisinos University, Brazil; André Luiz Durante Spigolon, Petrobras Research and Development Center (CENPES), Brazil; Luiz Gonzaga Jr, Maurício Roberto Veronez, Unisinos University, Brazil
TU2.MM-8.7: Global Spatial and Local Spectral Similarity based Sample Augment and Extended Subspace Projection for Hyperspectral Image Classification
Xueji Shen, Haoyang Yu, Chunyan Yu, Yulei Wang, Meiping Song, Dalian Maritime University, China
TU2.MM-8.8: Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning
Yanling Miao, Qi Wang, Mulin Chen, Xuelong Li, Northwestern Polytechnical University, China
TU2.MM-8.9: HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON CLASS CONFUSION MERGING AND SOFT BAND SELECTION
Xinyuan Miao, Ye Zhang, Junping Zhang, Xuejian Liang, Harbin Institute of Technology, China
TU2.MM-8.10: AUTOMATICALLY ADJUSTABLE MULTI-SCALE FEATURE EXTRACTION FRAMEWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Jiaqi Yang, Bo Du, Chen Wu, Liangpei Zhang, Wuhan University, China

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