Ansätze zur lokalen Bayes’schen Fusion von Informationsbeiträgen heterogener Quellen
| dc.contributor.author | Sander, Jennifer | |
| dc.date.accessioned | 2025-03-08T03:21:49Z | |
| dc.date.available | 2025-03-08T03:21:49Z | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-05-27T09:28:33Z | |
| dc.identifier | ONIX_20210527_9783731510628_34 | |
| dc.identifier | 1614-3914 | |
| dc.identifier | https://library.oapen.org/handle/20.500.12657/48837 | |
| dc.identifier.uri | https://doab-dev.siscern.org/handle/20.500.12854/177172 | |
| dc.description.abstract | 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. | |
| dc.language | German | |
| dc.relation.ispartofseries | Karlsruher Schriften zur Anthropomatik | |
| dc.rights | open access | |
| dc.subject.classification | bic Book Industry Communication::U Computing & information technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists | |
| dc.subject.other | Informationsfusion | |
| dc.subject.other | heterogene Informationsquellen | |
| dc.subject.other | Bayes’sche Theorie | |
| dc.subject.other | Prinzip der Maximalen Entropie | |
| dc.subject.other | Unsicherheit | |
| dc.subject.other | information fusion | |
| dc.subject.other | heterogeneous information sources | |
| dc.subject.other | Bayesian theory | |
| dc.subject.other | Maximum Entropy principle | |
| dc.subject.other | uncertainty | |
| dc.subject.other | thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists | |
| dc.title | Ansätze zur lokalen Bayes’schen Fusion von Informationsbeiträgen heterogener Quellen | |
| dc.type | book | |
| oapen.identifier.doi | 10.5445/KSP/1000125447 | |
| oapen.relation.isPublishedBy | 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 | |
| oapen.relation.isbn | 9783731510628 | |
| oapen.pages | 342 | |
| oapen.place.publication | Karlsruhe | |
| dc.seriesnumber | 45 | |
| dc.abstractotherlanguage | 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. | |
| dc.anonymity | All identities known | |
| dc.peerreviewid | 51a542ec-eaeb-47c2-861d-6022e981a97a | |
| dc.peerreviewtitle | Dissertations in Series (Dissertationen in Schriftenreihe) | |
| dc.openreview | No | |
| dc.responsibility | Books or series editor | |
| dc.stage | Pre-publication | |
| dc.reviewtype | Full text | |
| dc.reviewertype | Editorial board member | |
| dc.reviewertype | External peer reviewer |
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