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...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
मुख्य लेखक: Anneken, Mathias (auth)
स्वरूप: इलेक्ट्रोनिक पुस्तक अध्याय
प्रकाशित: KIT Scientific Publishing 2023
श्रृंखला:Karlsruher Schriften zur Anthropomatik
विषय:
ऑनलाइन पहुंच:DOAB: download the publication
DOAB: description of the publication
टैग: टैग जोड़ें
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
विवरण
सारांश: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.
भौतिक वर्णन:1 electronic resource (264 p.)
आईएसबीएन:KSP/1000158519
अभिगमन:Open Access