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Detecting anomalous behavior in sea traffic: A study of analytical strategies and their implications for surveillance systems
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2900-9335
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-8884-2154
2014 (English)In: International Journal of Information Technology and Decision Making, ISSN 0219-6220, ISSN 0219-6220, Vol. 13, no 2, p. 317-360Article in journal (Refereed) Published
Place, publisher, year, edition, pages
World Scientific, 2014. Vol. 13, no 2, p. 317-360
Keywords [en]
analytical reasoning, Anomaly detection, decision making, maritime traffic monitoring
National Category
Human Computer Interaction Computer Sciences
Research subject
Technology; Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-9031DOI: 10.1142/S021962201450045XISI: 000336410700005Scopus ID: 2-s2.0-84894705090OAI: oai:DiVA.org:his-9031DiVA, id: diva2:715176
Available from: 2014-05-01 Created: 2014-05-01 Last updated: 2018-03-28Bibliographically approved

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Riveiro, MariaFalkman, Göran

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