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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| Format: | eBook |
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KIT Scientific Publishing
2023
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| Series: | Karlsruher Schriften zur Anthropomatik
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | 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. |
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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/ |
| Physical Description: | 1 electronic resource (264 p.) |
| ISBN: | 9783731513001 1000158519 |