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Anomaliedetektion in räumlich-zeitlichen Datensätzen

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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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Bibliographic Details
Main Author: Anneken, Mathias (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2023
Series:Karlsruher Schriften zur Anthropomatik
Subjects:
Maths for computer scientists
spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen
Online Access:DOAB: download the publication
DOAB: description of the publication
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