LEADER 01996nam  2200457z- 450 
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010   $a1000125447
035   $a(CKB)5470000000567031
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/70092
035   $a(oapen)doab70092
035   $a(EXLCZ)995470000000567031
100   $a20202105d2021      |y         0
101 0 $ager
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aAnsa?tze zur lokalen Bayes'schen Fusion von Informationsbeitra?gen heterogener Quellen
210   $aKarlsruhe$cKIT Scientific Publishing$d2021
215   $a1 online resource (342 p.)
225 1 $aKarlsruher Schriften zur Anthropomatik
311 08$a3-7315-1062-6 
330   $aThe 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.
606   $aMaths for computer scientists$2bicssc
610   $aBayes'sche Theorie
610   $aBayesian theory
610   $aheterogene Informationsquellen
610   $aheterogeneous information sources
610   $ainformation fusion
610   $aInformationsfusion
610   $aMaximum Entropy principle
610   $aPrinzip der Maximalen Entropie
610   $auncertainty
610   $aUnsicherheit
615  7$aMaths for computer scientists
700   $aSander$b Jennifer$4auth$01300211
906   $aBOOK
912   $a9910476899203321
996   $aAnsätze zur lokalen Bayes?schen Fusion von Informationsbeiträgen heterogener Quellen$93025439
997   $aUNINA