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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Hoofdauteur: | |
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Formaat: | Elektronisch Hoofdstuk |
Gepubliceerd in: |
KIT Scientific Publishing
2023
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Reeks: | Karlsruher Schriften zur Anthropomatik
51 |
Onderwerpen: | |
Online toegang: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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DOAB: description of the publication
Anomaliedetektion in räumlich-zeitlichen Datensätzen
Gepubliceerd in 2023
DOAB: download the publication
DOAB: description of the publication
Elektronisch
Hoofdstuk