International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

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 Standard 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, 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