International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

FR2.MM-5: Deep Learning for Remotely Sensed Image Analysis
Fri, 16 Jul, 11:00 - 12:10 (UTC)
Fri, 16 Jul, 13:00 - 14:10 Central Europe Summer Time (UTC +2)
Fri, 16 Jul, 19:00 - 20:10 China Standard Time (UTC +8)
Fri, 16 Jul, 07:00 - 08:10 Eastern Standard Time (UTC -4)
Session Co-Chairs: Qian Du, Mississippi State University and Jennifer Adams, ESA
Session Manager: Christel Chappuis
Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

FR2.MM-5.1: A FILTERING APPROACH FOR GENERATED SAMPLES BY GANS IN SAR ATR

Changjie Cao, Zongyong Cui, Zongjie Cao, Liying Wang, Jielei Wang, Jianyu Yang, University of Electronic Science and Technology of China, China

FR2.MM-5.2: AUTOMATED COUNTING WILD BIRDS ON UAV IMAGE USING DEEP LEARNING

Kenta Ogawa, Rakuno Gakuen University, Japan; Yuting Lin, Hiroshi Takeda, Kanji Hashimoto, Kokusai Kogyo Co., Ltd, Japan; Yukiko Konno, Kaori Mori, Rakuno Gakuen University, Japan

FR2.MM-5.3: ADVERSARIAL ROBUSTNESS EVALUATION OF DEEP CONVOLUTIONAL NEURAL NETWORK BASED SAR ATR ALGORITHM

HAO SUN, YANJIE XU, GANGYAO KUANG, National University of Defense Technology, China; JIN CHEN, Beijing Institute of Remote Sensing Information, China

FR2.MM-5.4: ISAR IMAGES GENERATION VIA GENERATIVE ADVERSARIAL NETWORKS

Ruo-Yi Zhou, Zhi-Long Yang, Feng Wang, Fudan University, China

FR2.MM-5.5: OIL DEPOT DETECTION VIA CNN SEMANTIC SEGMENTATION

Antoine Tadros, Sébastien Drouyer, Rafael Grompone von Gioi, Centre Borreli - ENS Paris-Saclay, France

FR2.MM-5.6: SIAMMRAAN : SIAMESE MULTI-LEVEL RESIDUAL ATTENTION ADAPTIVE NETWORK FOR HYPERSPECTRAL VIDEO TRACKING

Ye Wang, Shaohui Mei, Shun Zhang, Northwestern Polytechnical University, China; Qian Du, Mississippi State University, United States

FR2.MM-5.7: TRANSFERRED TENSOR DECOMPOSITION-BASED DEEP LEARNING FOR HYPERSPECTRAL ANOMALY DETECTION

Yulei Wang, Fengchao Wang, Qingyu Zhu, Meiping Song, Chunyan Yu, Dalian Maritime University, China

FR2.MM-5.9: urban FOREST IDentification from high-resolution images using deep-learning method

Wei WANG, Rongyuan LIU, China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, China; Huiyun YANG, China Research Institute of Radioware Propagation, China; Ping ZHOU, China University of Geosciences-Beijing, China; Xiangwen ZHANG, Ling DING, China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, China

FR2.MM-5.10: SAR Image Change Detection via a Few-Shot Learning-based Neural Network

Ronfang Wang, Weidong Wang, Xidian Univerisity, China; Pinghai Dong, Tsinghua Shenzhen International Graduate School, China; Haojiang Wei, Licheng Jiao, Jia-Wei Chen, Xidian Univerisity, China