Anomaliedetektion in räumlich-zeitlichen Datensätzen

Human support in surveillance tasks is crucial due to the overwhelming amount of sensor data. This work focuses on the development of data fusion methods using the maritime domain as an example. Various anomalies are investigated, evaluated using real vessel traffic data and tested with experts. For...

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Bibliografiske detaljer

Hovedforfatter:	Anneken, Mathias
Format:	Online
Sprog:	tysk
Udgivet:	KIT Scientific Publishing 2023
Fag:	spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen
Online adgang:	OCN: 1403109722
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