Slide Fifth
Slide Second
Slide Fourth
Slide Sixth
Slide Sixth
International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

WE2.MM-9.5

MACHINE LEARNING-BASED PARADIGM FOR BOOSTING THE SEMANTIC ANNOTATION OF EO IMAGES

Corneliu Octavian Dumitru, Gottfried Schwarz, Chandrabali Karmakar, Mihai Datcu, German Aerospace Center (DLR), Germany
Session:
SAR and PolSAR Image Classification
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Wed, 14 Jul, 11:20-11:25 (UTC)
Wed, 14 Jul, 13:20-13:25 Central Europe Summer Time (UTC +2)
Wed, 14 Jul, 19:20-19:25 China Standard Time (UTC +8)
Wed, 14 Jul, 07:20-07:25 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Ronny Hänsch, German Aerospace Center and Florence Tupin, Telecom Paris
Session Manager:
Miguel Hoyo García
Presentation
Discussion
Resources
Session WE2.MM-9
WE2.MM-9.1: DEEP GRAPH CLUSTER BASED UNSUPERVISED REPRESENTATION LEARNING FOR POLSAR IMAGE CLASSIFICATION
Rui Tang, Xin Xu, Rui Yang, Rong Gui, Wuhan University, China
WE2.MM-9.2: TRIPLET ATTENTION FEATURE FUSION NETWORK FOR SAR AND OPTICAL IMAGE LAND COVER CLASSIFICATION
Zhe Xu, Northwestern Polytechnical University, China; Jinbiao Zhu, Chinese Academy of Sciences, China; Jie Geng, Xinyang Deng, Wen Jiang, Northwestern Polytechnical University, China
WE2.MM-9.3: Multi-category SAR Images Generation Based on Improved Generative Adversarial Network
Shaoyan Du, Jun Hong, Yu Wang, Kaichu Xing, Tian Qiu, Aerospace Information Reasearch Institute, Chinese Academy of Sciences, China
WE2.MM-9.4: From Pixel to Superpixel: A Multi-Scale Strategy for Polarimetric SAR Image Classification
Xianyuan Wang, Mengsi Yang, Liying Wang, Zongjie Cao, Yiming Pi, University of Electronic Science and Technology of China, China
WE2.MM-9.5: MACHINE LEARNING-BASED PARADIGM FOR BOOSTING THE SEMANTIC ANNOTATION OF EO IMAGES
Corneliu Octavian Dumitru, Gottfried Schwarz, Chandrabali Karmakar, Mihai Datcu, German Aerospace Center (DLR), Germany
WE2.MM-9.6: SYNERGETIC USE OF DESCENDING AND ASCENDING SAR WITH OPTICAL DATA FOR IMPERVIOUS SURFACE MAPPING
Ji Cheng, Genyun Sun, Aizhu Zhang, Hang Fu, Zhijun Jiao, China University of Petroleum (East china), China; Yanjuan Yao, State Environmental Protection Key Laboratory of Satellite Remote Sensing, China
WE2.MM-9.7: DETECTION OF THE LEADS IN THE ARCTIC DRIFTING SEA ICE ON SAR IMAGES
Natalia Zakhvatkina, Vladimir Smirnov, Irina Bychkova, Valeriy Stepanov, Arctic and Antarctic Research Institute, Russia
WE2.MM-9.8: CV-MotionNet: Complex-Valued Convolutional Neural Network for SAR Moving Ship Targets Classification
Yun Zhang, Qinglong Hua, Yicheng Jiang, Hongbo Li, Dan Xu, Harbin Institute of Technology, China
WE2.MM-9.9: MULTI-SCALE SAR SHIP CLASSIFICATION WITH CONVOLUTIONAL NEURAL NETWORK
Xiaowo Xu, Xiaoling Zhang, Tianwen Zhang, University of Electronic Science and Technology of China, China

Quicklinks

Downloads

Programme guide