International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU1.O-2: Deep Learning Based Feature Extraction
Tue, 13 Jul, 08:30 - 10:00 (UTC)
Tue, 13 Jul, 10:30 - 12:00 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 16:30 - 18:00 China Standard Time (UTC +8)
Tue, 13 Jul, 04:30 - 06:00 Eastern Standard Time (UTC -4)
Session Chair: Liangpei Zhang, Wuhan University
Session Manager: Alexandru Neculai
Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

TU1.O-2.1: GENERALIZED SCALABLE NEIGHBORHOOD COMPONENT ANALYSIS FOR SINGLE AND MULTI-LABEL REMOTE SENSING IMAGE CHARACTERIZATION

Jian Kang, School of Electronic and Information Engineering, Soochow University, China; Ruben Fernandez-Beltran, Institute of New Imaging Technologies, University Jaume I, Spain; Antonio Plaza, Hyperspectral Computing Laboratory, University of Extremadura, Spain

TU1.O-2.2: MOATNET: REGISTRATION FOR MULTI-TEMPORAL OPTICAL REMOTE SENSING IMAGES USING DEEP CONVOLUTIONAL FEATURES

Chao Li, Yanan You, Jingyi Cao, Wenli Zhou, Beijing University of Posts and Telecommunications, China

TU1.O-2.3: HYPERSPECTRAL IMAGE DENOISING BASED ON MULTI-STREAM DENOISING NETWORK

Yan Gao, Feng Gao, Junyu Dong, Ocean University of China, China

TU1.O-2.4: LSTM-ADVERSARIAL AUTOENCODER FOR SPECTRAL FEATURE LEARNING IN HYPERSPECTRAL ANOMALY DETECTION

Tongbin Ouyang, Jinshen Wang, Xinyue Zhao, Shujie Wu, Beihang University, China

TU1.O-2.5: GRAPH REGULARIZED AUTOENCODER BASED FEATURE EXTRACTION FOR HYPERSPECTRAL IMAGE CLASSIFICATION

Xiaotian Fan, Jingzhou Chen, Yuntao Qian, Zhejiang University, China

TU1.O-2.6: HYPERSPECTRAL IMAGE SUPER-RESOLUTION BASED ON MULTISCALE RESIDUAL BLOCK AND MULTILEVEL FEATURE FUSION

Gang Yu, Feng Zhang, Ting Hu, Wei Li, Ran Tao, Beijing Institute of Technology, China