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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Bibliographic Details
Main Author: Anneken, Mathias
Format: eBook
Published: KIT Scientific Publishing 2023
Series:Karlsruher Schriften zur Anthropomatik
Subjects:
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
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653 |a spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen 
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520 |a 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 this purpose, situations of interest and anomalies are modelled and evaluated based on different machine learning methods.