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相关论文: AIS-LLM: A Unified Framework for Maritime Trajecto…

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In marine surveillance, distinguishing between normal and anomalous vessel movement patterns is critical for identifying potential threats in a timely manner. Once detected, it is important to monitor and track these vessels until a…

机器学习 · 计算机科学 2023-06-08 Md Asif Bin Syed , Imtiaz Ahmed

In recent years, maritime safety and efficiency become more and more important across the world. Automatic Identification System (AIS) tracks vessel movement by onboard transceiver and terrestrial and/or satellite base station. The data…

数据库 · 计算机科学 2016-10-14 Shangbo Mao , Enmei Tu , Guanghao Zhang , Lily Rachmawati , Eshan Rajabally , Guang-Bin Huang

In a world of global trading, maritime safety, security and efficiency are crucial issues. We propose a multi-task deep learning framework for vessel monitoring using Automatic Identification System (AIS) data streams. We combine recurrent…

机器学习 · 计算机科学 2019-04-24 Duong Nguyen , Rodolphe Vadaine , Guillaume Hajduch , René Garello , Ronan Fablet

The automatic identification system (AIS) reports vessels' static and dynamic information, which are essential for maritime traffic situation awareness. However, AIS transponders can be switched off to hide suspicious activities, such as…

信号处理 · 电气工程与系统科学 2020-02-13 Sandeep Kumar Singh , Frank Heymann

In order to improve the vessel's capacity and ensure maritime traffic safety, vessel intelligent trajectory prediction plays an essential role in the vessel's smart navigation and intelligent collision avoidance system. However, current…

计算机与社会 · 计算机科学 2023-04-05 Jin Chen , Xingchen Li , Ye Xiao , Hao Chen , Yong Zhao

We address the problem of transforming raw vessel trajectory data collected from AIS into structured and semantically enriched representations interpretable by humans and directly usable by machine reasoning systems. We propose a…

Data-driven methods open up unprecedented possibilities for maritime surveillance using Automatic Identification System (AIS) data. In this work, we explore deep learning strategies using historical AIS observations to address the problem…

计算机视觉与模式识别 · 计算机科学 2023-01-18 Samuele Capobianco , Leonardo M. Millefiori , Nicola Forti , Paolo Braca , Peter Willett

Accurate prediction of human behavior is crucial for AI systems to effectively support real-world applications, such as autonomous robots anticipating and assisting with human tasks. Real-world scenarios frequently present challenges such…

人机交互 · 计算机科学 2025-07-21 Kojiro Takeyama , Yimeng Liu , Misha Sra

While accurate traffic forecasting is vital for Intelligent Transportation Systems (ITS), effectively communicating predicted conditions via natural language for human-centric decision support remains a challenge and is often handled…

机器学习 · 计算机科学 2026-01-13 Zeming Du , Qitan Shao , Hongfei Liu , Yong Zhang

For decades, track association has been a challenging problem in marine surveillance, which involves the identification and association of vessel observations over time. However, the Automatic Identification System (AIS) has provided a new…

机器学习 · 计算机科学 2023-04-05 Md Asif Bin Syed , Imtiaz Ahmed

Maritime port inspection plays a critical role in ensuring safety, regulatory compliance, and operational efficiency in complex maritime environments. However, existing inspection methods often rely on manual operations and conventional…

机器人学 · 计算机科学 2026-01-21 Muhayy Ud Din , Waseem Akram , Ahsan B. Bakht , Irfan Hussain

Recently, Unmanned Aerial Vehicles (UAVs) are increasingly being investigated to collect sensory data in post-disaster monitoring scenarios, such as tsunamis, where early actions are critical to limit coastal damage. A major challenge is to…

The prosperity of artificial intelligence has aroused intensive interests in intelligent/autonomous navigation, in which path prediction is a key functionality for decision supports, e.g. route planning, collision warning, and traffic…

人工智能 · 计算机科学 2022-01-11 Enmei Tu , Guanghao Zhang , Shangbo Mao , Lily Rachmawati , Guang-Bin Huang

Maritime AIS (Automatic Identification Systems) data serve as a valuable resource for studying vessel behavior. This study proposes a methodology to analyze route between maritime points of interest and extract geo-referenced standard…

The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered. Such data comes from the oceans and their surface, such as Automatic Identification System (AIS) messages…

机器学习 · 计算机科学 2024-09-06 Gabriel Spadon , Martha D. Ferreira , Amilcar Soares , Stan Matwin

Ship trajectories from Automatic Identification System (AIS) messages are important in maritime safety, domain awareness, and algorithmic testing. Although the specifications for transmitting and receiving AIS messages are fixed, it is well…

应用统计 · 统计学 2024-08-26 Niklas Paulig , Ostap Okhrin

Digital testing has emerged as a key paradigm for the development and verification of autonomous maritime navigation systems, yet the availability of realistic and diverse safety-critical encounter scenarios remains limited. Existing…

机器学习 · 计算机科学 2026-03-31 Sijin Sun , Liangbin Zhao , Ming Deng , Xiuju Fu

Vessel trajectory data from the Automatic Identification System (AIS) is used widely in maritime analytics. Yet, analysis is difficult for non-expert users due to the incompleteness and complexity of AIS data. We present CLEAR, a…

In the evolving landscape of transportation systems, integrating Large Language Models (LLMs) offers a promising frontier for advancing intelligent decision-making across various applications. This paper introduces a novel 3-dimensional…

机器学习 · 计算机科学 2024-12-17 Dexter Le , Aybars Yunusoglu , Karn Tiwari , Murat Isik , I. Can Dikmen

Recent research in Large Language Models (LLMs), has had a profound impact across various fields, including mobility data science. This paper explores the and experiment with different approaches to using LLMs for analyzing AIS data. We…

机器学习 · 计算机科学 2025-09-03 Gaspard Merten , Gilles Dejaegere , Mahmoud Sakr
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