TUP.P1.5

SEMANTIC SEGMENTATION FOR REMOTE SENSING IMAGES BASED ON SWIN-TRANSFORMER AND MULTISCALE FEATURE REFINEMENT

Shengyu Zhu, Center for Development of Onboard Computers and Electronic Products, Institute of Control Engineering,, China
Session:
TUP.P1: Deep Learning for Remote Sensing of the Environment Poster
Track:
Data Analysis
Location:
Poster Area 1
Presentation Time:
Tue, 18 Jul, 14:15 - 15:45 Pacific Time (UTC -7)
Session Chair:
Joan Francesc Munoz-Martin, Jet Propulsion Laboratory / California Institute of Technology
Session Managers:
Ge Jiang and Lanying Wang and Ayoti Banerjee and Shubham Awasthi
Presentation
Discussion
Resources
No resources available.
Session TUP.P1
TUP.P1.1: Cirrus Cloud and Shadow Masking in Optical Satellite using Deep Learning for Small Land Holding Farmer Plots
Venkanna Babu Guthula, Praveen Pankajakshan, Elvin John, Aravind S, CropIn Technology Solutions, India
TUP.P1.2: TRAINING STRATEGIES OF CNN FOR LAND COVER MAPPING WITH HIGH RESOLUTION MULTI-SPECTRAL IMAGERY IN SENEGAL
Minh Tri Le, Konrad Wessels, George Mason University, United States; Jordan Caraballo-Vega, Margaret Wooten, Mark Carroll, Christopher Neigh, NASA Goddard Spaceflight Center, United States; Nathan Thomas, University of Maryland College Park, United States
TUP.P1.3: GEOREFERENCING THERMAL SATELLITE IMAGES BASED ON LAND COVER INFORMATION EXTRACTION
Mojgan Madadikhaljan, Michael Schmitt, University of Bundeswehr Munich, Germany
TUP.P1.4: SEMANTIC SEGMENTATION OF BURNED AREAS IN SENTINEL-2 SATELLITE IMAGES USING DEEP LEARNING MODELS
Anes Ouadou, David Huangal, J. Alex Hurt, Grant Scott, University of Missouri, Columbia, United States
TUP.P1.5: SEMANTIC SEGMENTATION FOR REMOTE SENSING IMAGES BASED ON SWIN-TRANSFORMER AND MULTISCALE FEATURE REFINEMENT
Shengyu Zhu, Center for Development of Onboard Computers and Electronic Products, Institute of Control Engineering,, China
TUP.P1.6: PIXEL-LEVEL ANNOTATION OF SPECIFIC TARGETS FOR LARGE-SCALE REMOTE SENSING IMAGES
Guolong Liu, Wei Hu, Fan Zhang, Beijing University of Chemical Technology, China
TUP.P1.7: WEAKLY-SUPERVISED ROI EXTRACTION METHOD BASED ON CONTRASTIVE LEARNING FOR REMOTE SENSING IMAGES
Lingfeng He, Mengze Xu, Jie Ma, Beijing Foreign Studies University, China
TUP.P1.8: A FAST METHOD FOR BUILDING LARGE-SCALE REMOTE SENSING IMAGE SEMANTIC SEGMENTATION DATASET
Penglong Li, Chongqing Geomatics and Remote Sensing Center，Central South University, China; Zezhong MA, Li Wen, Ying Ao, Yan HU, Ding Luo, Ziwei JIANG, Xiaolong Li, Tao Zhang, Chongqing Geomatics and Remote Sensing Center, China
TUP.P1.9: Semi-Supervised Semantic Generative Networks for Remote Sensing Image Segmentation
Wanxuan Lu, Jidong Jin, Xian Sun, Kun Fu, Aerospace Information Research Institute, Chinese Academy of Sciences, China
Resources
No resources available.