AIS-Based Vessel Trajectory Compression: A Systematic Review and Software Development
Author:
Affiliation:
1. Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, China
2. Department of Civil and Environmental Engineering, National University of Singapore, Singapore
Funder
National Key Research and Development Program of China
Excellent Youth Foundation of Hubei Scientific Committee
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/8782711/10345397/10636246.pdf?arnumber=10636246
Reference78 articles.
1. STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network
2. Scalable clustering of segmented trajectories within a continuous time framework: application to maritime traffic data
3. A Data-Driven Iterative Multi-Attribute Clustering Algorithm and Its Application in Port Congestion Estimation
4. Context learning from a ship trajectory cluster for anomaly detection
5. Vessel Trajectory Prediction in Maritime Transportation: Current Approaches and Beyond
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