Ship imaging trajectory extraction via an aggregated you only look once (YOLO) model
Maritime traffic community has paid a huge amount of focuses to establish maritime
intelligent transportation infrastructure for the purpose of enhancing maritime traffic safety …
intelligent transportation infrastructure for the purpose of enhancing maritime traffic safety …
Maritime traffic route detection framework based on statistical density analysis from AIS data using a clustering algorithm
JS Lee, HT Lee, IS Cho - IEEE Access, 2022 - ieeexplore.ieee.org
Maritime traffic routes by ships navigation vary according to country and geographic
characteristics, and they differ according to the characteristics of the ships. In ocean areas …
characteristics, and they differ according to the characteristics of the ships. In ocean areas …
[HTML][HTML] A data mining method for automatic identification and analysis of icebreaker assistance operation in ice-covered waters
Icebreaker assistance is a common but complex operation in ice-infested regions. Currently,
the operational decision-making and the decisions regarding the safety indicators are …
the operational decision-making and the decisions regarding the safety indicators are …
An adaptive threshold fast DBSCAN algorithm with preserved trajectory feature points for vessel trajectory clustering
X Bai, Z Xie, X Xu, Y Xiao - Ocean Engineering, 2023 - Elsevier
Vessel navigation pattern recognition plays an important role in the research of intelligent
transportation on water. Clustering using the data stored in The Automatic Identification …
transportation on water. Clustering using the data stored in The Automatic Identification …
A novel ship trajectory clustering method for Finding Overall and Local Features of Ship Trajectories
C Tang, M Chen, J Zhao, T Liu, K Liu, H Yan, Y Xiao - Ocean engineering, 2021 - Elsevier
Ship trajectory clustering is one of the main methods of ship trajectory mining based on AIS
data. However, there exist two main problems in trajectory clustering: One is the inherent …
data. However, there exist two main problems in trajectory clustering: One is the inherent …
Dynamic maritime traffic pattern recognition with online cleaning, compression, partition, and clustering of AIS data
Y Zhang, W Li - Sensors, 2022 - mdpi.com
Maritime traffic pattern recognition plays a major role in intelligent transportation services,
ship monitoring, route planning, and other fields. Facilitated by the establishment of …
ship monitoring, route planning, and other fields. Facilitated by the establishment of …
Trajectory clustering for SVR-based Time of Arrival estimation
Abstract Accurate vessel Time of Arrival (ToA) estimation is important for port operation and
resource management. In this paper, we propose a data-driven approach for estimating the …
resource management. In this paper, we propose a data-driven approach for estimating the …
[HTML][HTML] Extracting the maritime traffic route in Korea based on probabilistic approach using automatic identification system big data
JS Lee, IS Cho - Applied Sciences, 2022 - mdpi.com
To protect the environment around the world, we are actively developing ecofriendly energy.
Offshore wind farm generation installed in the sea is extremely large among various …
Offshore wind farm generation installed in the sea is extremely large among various …
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels
Automatic Identification System (AIS) messages are useful for tracking vessel activity across
oceans worldwide using radio links and satellite transceivers. Such data play a significant …
oceans worldwide using radio links and satellite transceivers. Such data play a significant …
A hybrid-clustering model of ship trajectories for maritime traffic patterns analysis in port area
L Liu, Y Zhang, Y Hu, Y Wang, J Sun… - Journal of Marine Science …, 2022 - mdpi.com
A hybrid-clustering model is presented for the probabilistic characterization of ship traffic and
anomaly detection. A hybrid clustering model was proposed to increase the efficiency of …
anomaly detection. A hybrid clustering model was proposed to increase the efficiency of …