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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU2.MM-6.5

SHIP DETECTION FROM OPTICAL REMOTE SENSING IMAGERY BASED ON SCENE CLASSIFICATION AND SALIENCY-TUNED RETINANET

Ruoting Yin, Beijing University of Chemical Technology, China; Qizhi Xu, Beijing Institute of Technology, China; Ding Yifang, Institute of Beijing Remote sensing Information, China
Session:
Ship Detection
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Tue, 13 Jul, 11:20-11:25 (UTC)
Tue, 13 Jul, 13:20-13:25 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 19:20-19:25 China Standard Time (UTC +8)
Tue, 13 Jul, 07:20-07:25 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Shitian He, National University of Defense Technology and Haipeng Wang, Fudan University
Session Manager:
Louise Delhaye
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Session TU2.MM-6
TU2.MM-6.1: SMALL SHIP DETECTION VIA DEFORMABLE CONVOLUTIONAL NETWORK
Yao Wang, Ganggang Dong, Hongwei Liu, Xidian University, China
TU2.MM-6.2: ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation
Shitian He, Huanxin Zou, Yingqian Wang, Runlin Li, Fei Cheng, National University of Defence Technology, China
TU2.MM-6.3: SHIP DETECTION AND RECOGNITION IN OPTICAL REMOTE SENSING IMAGES BASED ON SCALE ENHANCEMENT ROTATING CASCADE R-CNN NETWORKS
Caiguang Zhang, Gangyao Kuang, Boli Xiong, National University of Defence Technology, China
TU2.MM-6.4: YOLOV3 BASED SHIP DETECTION IN VISIBLE AND INFRARED IMAGES
Lena Chang, Yi-Ting Chen, Ming-Hung Hung, Jung-Hua Wang, National Taiwan Ocean University, Taiwan; Yang-Lang Chang, National Taipei University of Technology, Taiwan
TU2.MM-6.5: SHIP DETECTION FROM OPTICAL REMOTE SENSING IMAGERY BASED ON SCENE CLASSIFICATION AND SALIENCY-TUNED RETINANET
Ruoting Yin, Beijing University of Chemical Technology, China; Qizhi Xu, Beijing Institute of Technology, China; Ding Yifang, Institute of Beijing Remote sensing Information, China
TU2.MM-6.6: IDENTIFICATION OF UNCLASSIFIED SHIPS IMPLEMENTING AIS INFORMATION AND SAR IMAGE-BASED SHIP DETECTION RESULTS
Juyoung Song, Duk-jin Kim, Seoul National University, Korea (South)
TU2.MM-6.7: SHIP DETECTION AND CLASSIFICATION IN EO/IR VHR SATELLITE IMAGERY
Igor Zakharov, C-CORE, Canada; Daniel Lavigne, DRDC, Canada; Sherry Warren, Michael Henschel, Desmond Power, Mark Howell, C-CORE, Canada
TU2.MM-6.8: SAR SHIP DETECTION BASED ON AN IMPROVED FASTER R-CNN USING DEFORMABLE CONVOLUTION
Xiao Ke, Xiaoling Zhang, Tianwen Zhang, Jun Shi, Shunjun Wei, University of Electronic Science and Technology of China, China
TU2.MM-6.9: FAST SHIP DETECTION METHOD FOR SAR IMAGES IN THE INSHORE REGION
Xiaoya Fu, Zhaocheng Wang, Hebei University of Technology, China
TU2.MM-6.10: A FEATURE ENHANCEMENT METHOD BASED ON THE SUB-APERTURE DECOMPOSITION FOR ROTATING FRAME SHIP DETECTION IN SAR IMAGES
Songlin Lei, Xiaolan Qiu, Chibiao Ding, Aerospace Information Reasearch Institute, Chinese Academy of Sciences, China; Shujie Lei, Shanghai Radio Equipment Research Institute, China

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