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Atefe Sedaghat, Homayoon Arbabkhah, Masood Jafari Kang and Maryam Hamidi
This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to...
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Bakht Zaman, Dusica Marijan and Tetyana Kholodna
The availability of automatic identification system (AIS) data for tracking vessels has paved the way for improvements in maritime safety and efficiency. However, one of the main challenges in using AIS data is often the low quality of the data. Practica...
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Jufu Zhang, Xujie Ren, Huanhuan Li and Zaili Yang
Automatic Identification System (AIS) equipment can aid in identifying ships, reducing ship collision risks and ensuring maritime safety. However, the explosion of massive AIS data has caused increasing data processing challenges affecting their practica...
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Tianyu Yang, Xin Wang and Zhengjiang Liu
With the aim to solve the problem of missing or tampering of ship type information in AIS information, in this paper, a novel ship type recognition scheme based on ship navigating trajectory and convolutional neural network (CNN) is proposed. Firstly, ac...
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Kwang-il Kim and Keon Myung Lee
Marine resources are valuable assets to be protected from illegal, unreported, and unregulated (IUU) fishing and overfishing. IUU and overfishing detections require the identification of fishing gears for the fishing ships in operation. This paper is con...
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