TUP1.PP.2
OIL TANK DETECTION BASED ON SEMI-DENSE CONNECTION STRATEGY AND DILATED CONVOLUTION FOR SAR IMAGES
Libao Zhang, Lan Zhang, Beijing Normal University, China
Session:
TUP1.PP: SAR Image Segmentation Poster
Track:
Data Analysis
Location:
Poster Area
Presentation Time:
Tuesday, 5 August, 09:15 - 10:30
Presentation
Discussion
Resources
No resources available.
Session TUP1.PP
TUP1.PP.1: SAR IMAGE CLASSIFICATION USING NEURAL NETWORKS AND GI0 DATA
Andrea Rey, Juliana Gambini, Emiliano Churruca, Universidad Nacional de Hurlingham, Argentina; Alejandro C. Frery, Victoria University of Wellington, New Zealand; Juan Santos, Universidad Nacional de Hurlingham, Argentina
TUP1.PP.2: OIL TANK DETECTION BASED ON SEMI-DENSE CONNECTION STRATEGY AND DILATED CONVOLUTION FOR SAR IMAGES
Libao Zhang, Lan Zhang, Beijing Normal University, China
TUP1.PP.3: A NOVEL RUNWAY AREA DETECTION NETWORK IN POLSAR IMAGES BASED ON SEMI- SUPERVISED LEARNING
Ping Han, Zhizheng Zhang, Jielong Zhou, Ruihua Liu, Cheng Fang, Civil Aviation University of China, China
TUP1.PP.4: CLSMNET: CROSS-LEVEL SEMANTIC MAPPING NETWORK FOR BUILDING EXTRACTION IN COMPLEX SCENES
Yu Liu, Haochi Ma, Xidian University, China; Erlong Wei, China Electronics Technology Group Corporation, China; Jing Bai, Zheng Chen, Xidian University, China; Bing Bai, Fudan University, China; Yu Lei, Northwestern Polytechnical University, China
TUP1.PP.5: A NOVEL POLSAR IMAGE ENHANCEMENT ALGORITHM FOR SEMANTIC SEGMENTATION
Xinwei An, Kangxin Xiong, Hongcheng Zeng, Xiaojie Zhou, Jie Chen, Wei Yang, Beihang University, China
TUP1.PP.6: LAND USE AND LAND COVER SEGMENTATION OF X-BAND SAR USING DEEP LEARNING TECHNIQUES
, ; Nitish Jaiswal, Clement Barras, Pradeep Kambhampati, Synspective, Japan
TUP1.PP.7: FEW-SHOT ISAR IMAGE SEGMENTATION USING 4D CONVOLUTIONAL TRANSFORMER
Haoran Sun, Feng Wang, Fudan University, China
TUP1.PP.8: CIT: A CROSS-MODAL INTERACTION TRANSFORMER NETWORK BASED ON MULTI-SOURCE REMOTE SENSING IMAGES
Zhonghuai Zhou, Liansong Zhang, Linxin Wang, Hongtao Shi, Fengkai Lang, Jinqi Zhao, China University of Mining and Technology, China
TUP1.PP.9: A DEEP LEARNING APPROACH TO FIELD BOUNDARY SEGMENTATION USING VERY HIGH-RESOLUTION X-BAND SAR DATA
Shaunak De, Victor Cazcarra-Bes, Yuriy Goncharenko, Jay McDaniel, Craig Stringham, Capella Space, United States
TUP1.PP.10: Evaluating Segmentation Performance of Learnable Resized Models on Small and Sparse Features
Miguel Luis Lagahit, Institute of Science Tokyo, Japan; Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, National Institute of Advanced Industrial Science and Technology, Japan; Masashi Matsuoka, Institute of Science Tokyo, Japan
Resources
No resources available.