Wissensbasierte probabilistische Modellierung für die Situationsanalyse am Beispiel der maritimen Überwachung

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-...

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Bibliographic Details
Main Author: Fischer, Yvonne (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2016
Series: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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245 1 0 |a Wissensbasierte probabilistische Modellierung für die Situationsanalyse am Beispiel der maritimen Überwachung 
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520 |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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546 |a German 
653 |a data fusion 
653 |a dynamic Bayesian networks 
653 |a SituationsbewusstseinSituation assessment 
653 |a maritime surveillance 
653 |a maritime Überwachung 
653 |a Situationsanalyse 
653 |a Datenfusion 
653 |a situation awareness 
653 |a dynamische Bayes'sche Netze 
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