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oapen-20.500.12657-488372021-05-28T00:58:07Z Ansätze zur lokalen Bayes’schen Fusion von Informationsbeiträgen heterogener Quellen Sander, Jennifer Informationsfusion heterogene Informationsquellen Bayes’sche Theorie Prinzip der Maximalen Entropie Unsicherheit information fusion heterogeneous information sources Bayesian theory Maximum Entropy principle uncertainty bic Book Industry Communication::U Computing & information technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists 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. 2021-05-27T09:28:33Z 2021-05-27T09:28:33Z 2021 book ONIX_20210527_9783731510628_34 1614-3914 9783731510628 https://library.oapen.org/handle/20.500.12657/48837 ger Karlsruher Schriften zur Anthropomatik application/pdf n/a ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf KIT Scientific Publishing 10.5445/KSP/1000125447 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. 10.5445/KSP/1000125447 44e29711-8d53-496b-85cc-3d10c9469be9 9783731510628 45 342 Karlsruhe open access
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OAPEN
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ger
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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.
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| title |
ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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| title_full |
ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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| title_fullStr |
ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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ansatze-zur-lokalen-bayesschen-fusion-von-informationsbeitragen-heterogener-quellen.pdf
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KIT Scientific Publishing
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2021
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1771297549781565440
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