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International Geoscience and Remote Sensing Symposium
In 2021 a joint initiative of Belgium and The Netherlands
Technical Program
Session TH3.O-9
TH3.O-9: Deep Learning for Remote Sensing Image Classification and Clustering
Thu, 15 Jul, 12:25 - 13:55 (UTC)
Thu, 15 Jul, 14:25 - 15:55 Central Europe Summer Time (UTC +2)
Thu, 15 Jul, 20:25 - 21:55 China Standard Time (UTC +8)
Thu, 15 Jul, 08:25 - 09:55 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Mario Parente, University of Massachusetts, Amherst and Shutao Li, Hunan University
Session Manager:
Ines Meraoumia
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
TH3.O-9.1: DDIPNET AND DDIPNET+: DISCRIMINANT DEEP IMAGE PRIOR NETWORKS FOR REMOTE SENSING IMAGE CLASSIFICATION
Daniel Santos, Rafael Pires, Leandro Passos, Joao Papa, Sao Paulo State University, Brazil
TH3.O-9.2: AN END-TO-END CLUSTERING FRAMEWORK BASED ON DYNAMIC THRESHOLD FOR SAR IMAGES
Mengsi Yang, Junchuan Guo, Xianyuan Wang, Zongjie Cao, Zongyong Cui, University of Electronic Science and Technology of China, China
TH3.O-9.3: SEMI-SUPERVISED GRAPH PROTOTYPICAL NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Bobo Xi, Jiaojiao Li, Yunsong Li, Xidian University, China; Qian Du, Mississippi State University, United States
TH3.O-9.4: CROSS-MODAL FEATURE FUSION RETRIEVAL FOR REMOTE SENSING IMAGE-VOICE RETRIEVAL
Rui Yang, Yu Gu, Yu Liao, Huan Zhang, Yingzhi Sun, Shuang Wang, Xidian University, China; He Zhang, Northwest University, China; Biao Hou, Licheng Jiao, Xidian University, China
TH3.O-9.5: IMPROVED DEEP CLUSTERING OF MASTCAM IMAGES USING METRIC LEARNING
Tejas Panambur, Mario Parente, University of Massachusetts Amherst, United States
TH3.O-9.6: IMPROVING LAND COVER CLASSIFICATION WITH A SHIFT-INVARIANT CENTER-FOCUSING CONVOLUTIONAL NEURAL NETWORK
Cong Luo, Technical University of Munich, Germany; Yuansheng Hua, Lichao Mou, Xiao Xiang Zhu, Technical University of Munich & German Aerospace Center, Germany
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