MOP1.PL.9
ADVANCING SURVEILLANCE IN MARITIME DOMAIN WITH SHIP WAKE DETECTION
Andrea Mazzeo, Angela Carmen Cristofano, Maria Daniela Graziano, Università Degli Studi Di Napoli Federico II, Italy; Giuliano Vernengo, Università degli studi di Genova, Italy; Davide Bonaldo, Consiglio Nazionale delle Ricerche, Italy; Diego Villa, Università degli studi di Genova, Italy; Gian Marco Scarpa, Federica Braga, Paolo Vavasori, Consiglio Nazionale delle Ricerche (CNR), Italy
Session:
MOP1.PL: Ship Detection and Recognition Poster
Track:
Data Analysis
Location:
Poster Area
Presentation Time:
Monday, 4 August, 14:15 - 15:45
Presentation
Discussion
Resources
No resources available.
Session MOP1.PL
MOP1.PL.1: TPU-Enabled SAR Image Processing in Satellites for Maritime Surveillance
Grace Bocek, Univesity of Minnesota Twin Cities, United States; Bharadwaj Madabhushi, Sandip Kundu, University of Massachusetts Amherst, United States
MOP1.PL.2: An Aperture Selection Method for ISAR imaging of Ship Targets under Long-Term High Sea States
Jiaqi Lei, Beijing Institute of Technology, China; ShuJiang Liu, Beijing Institute of Electronic Engineering, China; Han Li, Beijing Institute of Technology, China
MOP1.PL.3: Weak Target Detection in Radar Sea Clutter Based on Weighted Convex Hull Tree Algorithm
Zi-Xun Guo, Kang-Hui Wu, Northwestern Polytechnical University, China; Xiao-Hui Bai, Xi’an University of Finance and Economics, China; Jia Su, Yi-Fei Fan, Northwestern Polytechnical University, China; Peng-Lang Shui, Xidian University, China
MOP1.PL.4: Weather Radar Based Ship Detection and Feasibility Verification
Yichi Gu, Xichao Dong, Jiacheng Yang, Beijing Institute of Technology, China
MOP1.PL.5: EFFECT ANALYSIS OF SHIP EQUIVALENT CENTROID EXTRACTION UNDER MULTI IMAGING ANGLES
Yihang Zhi, Bing Sun, Mingqing Han, Beihang University, China
MOP1.PL.6: BOWSTERN R-CNN: A BOW-ORIENTATION-SENSITIVE SHIP OBJECT DETECTOR USING KEYPOINTS
Qianfang Wang, Bo Ren, Chongyu Wang, Biao Hou, Xidian University, China
MOP1.PL.7: ENERGY-EFFICIENT ATTENTION-BASED SPIKING YOLO NETWORK FOR SAR SHIP DETECTION
Zihan Wang, Yanxin Lu, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Jinxin Li, School of Electronic, Electrical and Communication Engineering, University of Chinese Academyof Sciences, China; Bingchen Zhang, Aerospace Information Research Institute, Chinese Academy of Sciences, China
MOP1.PL.8: ROSD-SAR: ROBUST SHIP DETECTION IN SAR IMAGES WITH NOISY BOX
Pengfei Guo, Sen Lei, Southwest Jiaotong University, China; Chengxin Liu, Huazhong University of Science and Technology, China; Nanqing Liu, Heng-Chao Li, Southwest Jiaotong University, China
MOP1.PL.9: ADVANCING SURVEILLANCE IN MARITIME DOMAIN WITH SHIP WAKE DETECTION
Andrea Mazzeo, Angela Carmen Cristofano, Maria Daniela Graziano, Università Degli Studi Di Napoli Federico II, Italy; Giuliano Vernengo, Università degli studi di Genova, Italy; Davide Bonaldo, Consiglio Nazionale delle Ricerche, Italy; Diego Villa, Università degli studi di Genova, Italy; Gian Marco Scarpa, Federica Braga, Paolo Vavasori, Consiglio Nazionale delle Ricerche (CNR), Italy
MOP1.PL.10: SAR Imaging of Swing Ship Based on Physical Struecture-guided Segmentation
Jiayan Ouyang, Jindong Yu, Mugen Peng, Beijing University of Posts and Telecommunications, China; Ze Yu, Beihang University, China; Jinjun Tian, Chongqing Cewei Technology Co.Ltd, China
MOP1.PL.11: TOWARDS GENERALIZED SAR SHIP DETECTION VIA RANDOMIZED FEATURE STATISTIC MODELING AND CONTRASTIVE INVARIANCE LEARNING
Shuang Liu, Dong Li, Chongqing University, China; Haibo Song, Caizhi Fan, National University of Defense Technology, China; Ke Li, Naval University of Engineering, China
MOP1.PL.12: A NOVEL SHIP RECOGNITION METHOD BASED ON MULTI-SOURCE IMAGE FUSION
Xueying Yang, Gaopeng Li, Yun Zhang, Harbin Institute of Technology, China
Resources
No resources available.