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Authors: Akash Kumar ; Aayush Sugandhi and Yamuna Prasad

Affiliation: Indian Institute of Technology Jammu, India

Keyword(s): Automatic Identification System (AIS), VGG16, Faster RCNN, MMSI Number, Draught Weight, Blind Period, Port Call.

Abstract: This paper addresses the issue of vessel tracking using Automatic Identification Systems (AIS) and imagery data. In general, we depend on AIS data for the accurate tracking of the vessels, but there is often a gap between two consecutive AIS instances of any vessel. This is called as blind period or the inactivity period. In this period, we can not be sure about the location of the ship. The duration of inactivity period is quite variable due to various factors like weather, satellite connectivity and manual turn off. This makes tracking and identification of any threat difficult. In this paper, we propose a two-fold approach for tracking and identifying the potential threat using deep learning models and AIS data. In the first fold, the ships out of satellite imaging are identified while in the second fold, the corresponding AIS data is analysed to discover any potential threat or suspicious activity.

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Paper citation in several formats:
Kumar, A.; Sugandhi, A. and Prasad, Y. (2022). Detection and Identification of Threat Potential of Ships using Satellite Images and AIS Data. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 691-698. DOI: 10.5220/0010914600003124

@conference{visapp22,
author={Akash Kumar. and Aayush Sugandhi. and Yamuna Prasad.},
title={Detection and Identification of Threat Potential of Ships using Satellite Images and AIS Data},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={691-698},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010914600003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Detection and Identification of Threat Potential of Ships using Satellite Images and AIS Data
SN - 978-989-758-555-5
IS - 2184-4321
AU - Kumar, A.
AU - Sugandhi, A.
AU - Prasad, Y.
PY - 2022
SP - 691
EP - 698
DO - 10.5220/0010914600003124
PB - SciTePress