01996nam 2200457z- 450 9910476899203321202105281000125447(CKB)5470000000567031(oapen)https://directory.doabooks.org/handle/20.500.12854/70092(oapen)doab70092(EXLCZ)99547000000056703120202105d2021 |y 0gerurmn|---annantxtrdacontentcrdamediacrrdacarrierAnsätze zur lokalen Bayes'schen Fusion von Informationsbeiträgen heterogener QuellenKarlsruheKIT Scientific Publishing20211 online resource (342 p.)Karlsruher Schriften zur Anthropomatik3-7315-1062-6 The solution of various tasks benefits from information fusion or even requires it. The Bayesian fusion methodology is clear, well-founded and fulfills the essential requirements for a meaningful methodology also for fusing the contributions of heterogeneous information sources. In many practically relevant tasks, Bayesian methods cause high, often unacceptable effort. In the work, novel approaches to cope with Bayesian fusion in such situations are formulated and investigated.Maths for computer scientistsbicsscBayes'sche TheorieBayesian theoryheterogene Informationsquellenheterogeneous information sourcesinformation fusionInformationsfusionMaximum Entropy principlePrinzip der Maximalen EntropieuncertaintyUnsicherheitMaths for computer scientistsSander Jenniferauth1300211BOOK9910476899203321Ansätze zur lokalen Bayes’schen Fusion von Informationsbeiträgen heterogener Quellen3025439UNINA