[HTML][HTML] The application of artificial intelligence technology in shipping: A bibliometric review
Artificial intelligence (AI) technologies are increasingly being applied to the shipping
industry to advance its development. In this study, 476 articles published in the Science …
industry to advance its development. In this study, 476 articles published in the Science …
[HTML][HTML] Deep bi-directional information-empowered ship trajectory prediction for maritime autonomous surface ships
It is critical to have accurate ship trajectory prediction for collision avoidance and intelligent
traffic management of manned ships and emerging Maritime Autonomous Surface Ships …
traffic management of manned ships and emerging Maritime Autonomous Surface Ships …
Medical assisted-segmentation system based on global feature and stepwise feature integration for feature loss problem
This paper presents an advanced methodology that combines Convolutional Neural
Networks (CNNs) and Transformers to tackle the issue of feature loss and elevate …
Networks (CNNs) and Transformers to tackle the issue of feature loss and elevate …
[HTML][HTML] A hierarchical methodology for vessel traffic flow prediction using Bayesian tensor decomposition and similarity grouping
Accurate vessel traffic flow (VTF) prediction can enhance navigation safety and economic
efficiency. To address the challenge of the inherently complex and dynamic growth of the …
efficiency. To address the challenge of the inherently complex and dynamic growth of the …
[HTML][HTML] A data mining-then-predict method for proactive maritime traffic management by machine learning
Proactive traffic management is increasingly critical in maritime intelligent transportation
systems. Central to this is maritime traffic forecasting, which leverages specific structures …
systems. Central to this is maritime traffic forecasting, which leverages specific structures …
Adaptive collision avoidance decisions in autonomous ship encounter scenarios through rule-guided vision supervised learning
K Zheng, X Zhang, C Wang, Y Li, J Cui, L Jiang - Ocean Engineering, 2024 - Elsevier
Limitations are identified in the expressive capabilities of the deep feature extraction network
employed in deep reinforcement learning (DRL), particularly in complex scenarios …
employed in deep reinforcement learning (DRL), particularly in complex scenarios …
Optimizing anti-collision strategy for MASS: A safe reinforcement learning approach to improve maritime traffic safety
Maritime autonomous surface ships (MASS) promise enhanced efficiency, reduced human
errors, and to improve maritime traffic safety. However, MASS navigation in complex …
errors, and to improve maritime traffic safety. However, MASS navigation in complex …
[HTML][HTML] Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories
Abstract Automatic Identification System (AIS) offers a wealth of vessel navigation data,
which underpins research in maritime data mining, situational awareness, and knowledge …
which underpins research in maritime data mining, situational awareness, and knowledge …
RAGAN: A Generative Adversarial Network for risk-aware trajectory prediction in multi-ship encounter situations
C Jia, J Ma, X Yang, X Lv - Ocean Engineering, 2023 - Elsevier
Ship trajectory prediction plays a vital role in ensuring safety in dense waterway traffic.
However, conventional prediction methods often disregard the intricate spatial–temporal …
However, conventional prediction methods often disregard the intricate spatial–temporal …
[HTML][HTML] A hybrid deep learning method for the prediction of ship time headway using automatic identification system data
Abstract Ship Time Headway (STH) is used in maritime navigation to describe the time
interval between the arrivals of two consecutive ships in the same water area. This …
interval between the arrivals of two consecutive ships in the same water area. This …