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A joint statistical and symbolic anomaly detection system: Increasing performance in maritime surveillance
RISE., Swedish ICT, SICS.ORCID-id: 0000-0001-8577-6745
RISE., Swedish ICT, SICS.ORCID-id: 0000-0002-6797-8463
RISE., Swedish ICT, SICS.ORCID-id: 0000-0002-7181-8411
RISE., Swedish ICT, SICS.ORCID-id: 0000-0003-3909-6751
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2012 (Engelska)Ingår i: 15th International Conference on Information Fusion, FUSION 2012, 2012, s. 1919-1926, artikel-id 6290535Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The need for improving the capability to detect illegal or hazardous activities and yet reducing the workload of operators involved in various surveillance tasks calls for research on more capable automatic tools. To maximize their performance, these tools should be able to combine automatic capturing of normal behavior from data with domain knowledge in the form of human descriptions. In a proposed Joint Statistical and Symbolic Anomaly Detection System, statistical and symbolic methods are tightly integrated in order to detect the majority of critical events in the situation while minimizing unwanted alerts. We exemplify the proposed system in the domain of maritime surveillance.

Ort, förlag, år, upplaga, sidor
2012. s. 1919-1926, artikel-id 6290535
Nyckelord [en]
anomaly detection, data driven methods, knowledge driven methods, maritime domain awareness, situation assessement, statistical methods, surveillance, symbolic methods, Data-driven methods, Digital storage, Information fusion, Space surveillance, Monitoring
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Teknik och teknologier
Identifikatorer
URN: urn:nbn:se:ri:diva-51716Scopus ID: 2-s2.0-84867645582ISBN: 9780982443859 (tryckt)OAI: oai:DiVA.org:ri-51716DiVA, id: diva2:1517266
Konferens
15th International Conference on Information Fusion, FUSION 2012, 7 September 2012 through 12 September 2012, Singapore
Tillgänglig från: 2021-01-13 Skapad: 2021-01-13 Senast uppdaterad: 2023-05-09Bibliografiskt granskad

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Holst, AndersBjurling, BjörnEkman, JanRudström, Åsa

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