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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Bibliografische gegevens
Hoofdauteur: Anneken, Mathias (auth)
Formaat: Elektronisch Hoofdstuk
Gepubliceerd in: KIT Scientific Publishing 2023
Reeks:Karlsruher Schriften zur Anthropomatik 51
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