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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

WE2.MM-11.1

A patch tensor-based change detection method for hyperspectral images

Zengfu Hou, Wei Li, Beijing Institute of Technology, China; Qian Du, Mississippi State University, United States
Session:
Change Detection Techniques for Multi- and Hyper-spectral Data
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Wed, 14 Jul, 11:00-11:05 (UTC)
Wed, 14 Jul, 13:00-13:05 Central Europe Summer Time (UTC +2)
Wed, 14 Jul, 19:00-19:05 China Standard Time (UTC +8)
Wed, 14 Jul, 07:00-07:05 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
James Theiler, Los Alamos National Laboratory and Matthieu Molinier, VTT Technical Research Centre of Finland Ltd
Session Manager:
Hira Zafar
Presentation
Discussion
Resources
Session WE2.MM-11
WE2.MM-11.1: A patch tensor-based change detection method for hyperspectral images
Zengfu Hou, Wei Li, Beijing Institute of Technology, China; Qian Du, Mississippi State University, United States
WE2.MM-11.2: A novel hyperspectral image change detection framework based on 3D-Wavelet domain active convolutional neural network
Xianghai Wang, Chengdi Xing, Yining Feng, Ruoxi Song, Zhenhua Mu, Liaoning Normal University, China
WE2.MM-11.3: AN UNSUPERVISED CHANGE DETECTION APPROACH FOR DENSE SATELLITE IMAGE TIME SERIES USING 3D CNN
Khatereh Meshkini, Francesca Bovolo, Fondazione Bruno Kessler, Italy; Lorenzo Bruzzone, University of Trento, Italy
WE2.MM-11.4: HIGH-RESOLUTION REMOTE SENSING IMAGES CHANGE DETECTION WITH SIAMESE HOLISTICALLY-GUIDED FCN
Huayu Zhang, Xu Tang, Xidian University, China; Xiao Han, Geovis Spatial Technology Co.,Ltd, China; Jingjing Ma, Xiangrong Zhang, Licheng Jiao, Xidian University, China
WE2.MM-11.5: A spatial-temporal-channel attention Unet++ for high resolution remote sensing image change detection
Mingliang Liu, Jinjie Huang, Harbin University of Science and Technology, China; Lei Ma, Ling Wan, Institute of Automation, Chinese Academy of Sciences, China; Jialong Guo, Beijing University of Technology, China; Dongpan Yao, University of Chinese Academy of Sciences, China
WE2.MM-11.6: A SIAMESE GLOBAL LEARNING FRAMEWORK FOR MULTI-CLASS CHANGE DETECTION
Xi Guo, Qiqi Zhu, Weihuan Deng, Qingfeng Guan, China University Of Geosciences, China
WE2.MM-11.7: REMOTE SENSING IMAGE CHANGE DETECTION BASED ON FULLY CONVOLUTIONAL NETWORK WITH PYRAMID ATTENTION
Shujun Li, Lianzhi Huo, Aerospace Information Reasearch Institute, Chinese Academy of Sciences, China
WE2.MM-11.8: END-TO-END CHANGE DETECTION IN SATELLITE REMOTE SENSING IMAGERY
Meziane Iftene, Agence Spatiale Algérienne, Algeria; Mohammed El Amin Larabi, Algerian Space Agency, Algeria; Moussa Sofiane Karoui, Centre des Techniques Spatiales, Algeria
WE2.MM-11.9: Change analysis in registered satellite image time series
Tristan Dagobert, Rafael Grompone von Gioi, Université Paris-Saclay, France; Charles Hessel, Université Paris-Saclay & Kayrros, France; Jean-Michel Morel, Université Paris-Saclay, France; Carlo de Franchis, Université Paris-Saclay & Kayrros, France
WE2.MM-11.10: MULTI-OBJECTS CHANGE DETECTION BASED ON RES-UNET
Lang Yuan, Yuxia Li, Yu Si, Junmei Ren, Yizhuo Yang, Yushu Gong, Yongqiang Xia, Zhonggui Tong, Ling Tong, University of Electronic Science and Technology of China, China

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