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Bayesian fusion: Modeling and application

: Sander, Jennifer; Beyerer, Jürgen

Postprint urn:nbn:de:0011-n-2820606 (182 KByte PDF)
MD5 Fingerprint: 067333ce5f5069284f719f7bb8603bde
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Erstellt am: 3.4.2014

Institute of Electrical and Electronics Engineers -IEEE-; International Society of Information Fusion -ISIF-:
8th Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013 : 9-11 October 2013, Bonn
Piscataway, NJ: IEEE, 2013
ISBN: 978-1-4799-0777-9
6 S.
Workshop on Sensor Data Fusion (SDF) <8, 2013, Bonn>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Bayesian statistics leads to a powerful fusion methodology, especially for the fusion of heterogeneous information sources. If fusion problems are handled under consideration of the full expressiveness and the full range of methods provided by Bayesian statistics, the Bayesian fusion methodology possesses an impressive wide range of applications. We discuss this by having a closer look at selected aspects of Bayesian modeling. Thereby, also parallels to other methods used for information fusion will be drawn. With regard to the practical tractability of Bayesian fusion problems, selected approaches to deal with its potentially high complexity are discussed.