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|a 1000051065
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|a 9783731504603
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|a Fischer, Yvonne
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|a Wissensbasierte probabilistische Modellierung für die Situationsanalyse am Beispiel der maritimen Überwachung
|h Elektronische Ressource
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| 260 |
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|b KIT Scientific Publishing
|c 2016
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|a 1 electronic resource (XVI, 217 p. p.)
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|a situation awareness
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|a maritime surveillance
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|a maritime Überwachung
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|a SituationsbewusstseinSituation assessment
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|a data fusion
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|a dynamic Bayesian networks
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|a Datenfusion
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|a Situationsanalyse
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|a dynamische Bayes'sche Netze
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|a deu
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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|a Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe
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|a Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/
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|a 10.5445/KSP/1000051065
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|u https://directory.doabooks.org/handle/20.500.12854/62761
|z DOAB: description of the publication
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|u https://www.ksp.kit.edu/9783731504603
|7 0
|x Verlag
|3 Volltext
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|a In today's surveillance systems, a multitude of sensors are used. Thus, the data volume is clearly increasing and the human decision maker has to be supported in analyzing this data in an intelligent way. This contribution deals with the process of situation assessment, which is analyzing real-time data with respect to pre-modeled situations of interest with a dynamic Bayesian network. The quality of the recognition is evaluated with a maritime dataset.
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