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...
Bewaard in:
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| Formaat: | Elektronisch Hoofdstuk |
| Gepubliceerd in: |
KIT Scientific Publishing
2023
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| Reeks: | Karlsruher Schriften zur Anthropomatik
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| Onderwerpen: | |
| Online toegang: | DOAB: download the publication DOAB: description of the publication |
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Internet
DOAB: download the publicationDOAB: description of the publication
3rd Floor Main Library
| Plaatsingsnummer: |
A1234.567 |
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| Kopie 1 | Beschikbaar |