IEEE IGARSS 2022 || Kuala Lumpur, Malaysia || 17

MO6.V7: Classification and Clustering MMV I

Mon, 18 Jul, 21:35 - 22:45 Malaysia Time (UTC +8)
Mon, 18 Jul, 15:35 - 16:45 Central European Time (UTC +1)
Mon, 18 Jul, 13:35 - 14:45 UTC
Mon, 18 Jul, 09:35 - 10:45 Eastern Time (UTC -5)

Location: Virtual Room 7

Session Type: Multimedia Virtual

Session Co-Chairs: Benjamin Bischke, Vision Impluse GmbH and Masoud Mahdianpari, Memorial University of Newfoundland, Canada

Session Manager: Khe Kheng Kow

Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

MO6.V7.1: OPEN-SET CLASSIFICATION IN REMOTE SENSING IMAGERY WITH ENERGY-BASED VISION TRANSFORMER

Reham Al-Dayil, Yakoub Bazi, Naif Alajlan, King Saud Univirsity, Saudi Arabia

MO6.V7.2: LOSSY COMPRESSION OF THREE-CHANNEL REMOTE SENSING IMAGES WITH “COLOR” COMPONENT DOWNSCALING

Victor Makarichev, Galina Proskura, Oleksii Rubel, Vladimir Lukin, National Aerospace University, Ukraine; Benoit Vozel, Kacem Chehdi, University of Rennes 1, France

MO6.V7.3: WETLAND MAPPING BY JOINTLY USE OF CONVOLUTIONAL NEURAL NETWORK AND GRAPH CONVOLUTIONAL NETWORK

Hamid Jafarzadeh, Masoud Mahdianpari, Eric Gill, Memorial University of Newfoundland, Canada

MO6.V7.4: MAE-NET: A MICRO NETWORK ARCHITECTURE EVOLUTIONARY SEARCH METHOD FOR REMOTE SENSING IMAGE SCENE CLASSIFICATION

Yuting Wan, Yanfei Zhong, Ailong Ma, Junjue Wang, Liangpei Zhang, Wuhan University, China

MO6.V7.5: PROTOTYPE-BASED CLUSTERED FEDERATED LEARNING FOR SEMANTIC SEGMENTATION OF AERIAL IMAGES

Boning Zhang, Xiaokang Zhang, Man-On Pun, The Chinese University of Hong Kong, Shenzhen, China; Ming Liu, MizarVision, China

MO6.V7.6: REVIEW OF VISION TRANSFORMER MODELS FOR REMOTE SENSING IMAGE SCENE CLASSIFICATION

Pengyuan Lv, Wenjun Wu, Ningxia University, China; Yanfei Zhong, Liangpei Zhang, Wuhan University, China

MO6.V7.7: A SPATIAL ATTENTION GUIDED SCENE CLASSIFICATION METHOD FOR MULTISCALE REMOTE SENSING DATASET

Xinran Lyu, Libao Zhang, Beijing Normal University, China

MO6.V7.8: Manifold Augmentation Based Self-Supervised Contrastive Learning For Few-Shot Remote Sensing Scene Classification

Yunrui Sheng, Liang Xiao, Nanjing University of Science and Technology, China

MO6.V7.9: BAND WEIGHT ADAPTIVE CLASSIFICATION NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION

Yuchen Liang, Guihong Chen, Jiayi Guo, beijing big data center, China; Wang Yao, National Meteorological Information Centre, China

MO6.V7.10: RAPIDAI4EO: MONO- AND MULTI-TEMPORAL DEEP LEARNING MODELS FOR UPDATING THE CORINE LAND COVER PRODUCT

Priyash Bhugra, Benjamin Bischke, Christoph Werner, Robert Syrnicki, Carolin Packbier, Patrick Helber, Vision Impluse GmbH, Germany; Caglar Senaras, Akhil Singh Rana, Tim Davis, Annett Wania, Planet Labs GmbH, Germany; Wanda De Keersmaecker, Daniele Zanaga, Ruben Vandekerchove, VITO NV, Belgium; Giovanni Marchisio, Planet Labs PBC, United States