Ensemble Learning for Multi-source Information Fusion-Reference-Cited by-同舟云学术

Ensemble Learning for Multi-source Information Fusion

Published:2010 Issue: Volume: Page:123-141
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
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Author:

Beyer Jörg,Heesche Kai,Hauptmann Werner,Otte Clemens,Kruse Rudolf

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-11676-6_6.pdf

Reference27 articles.

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2. Bengio, S., Marcel, C., Marcel, S., Mariéthoz, J.: Confidence measures for multimodal identity verification. Information Fusion 3, 267–276 (2002)

3. Beyer, J., Heesche, K., Hauptmann, W., Otte, C.: Combined knowledge-based and data-driven modeling by heterogeneous mixture-of-experts. In: Mikut, R., Reischl, M. (Hrsg.) Workshop Computational Intelligence, vol. 18, pp. 225–236. Universitätsverlag Karlsruhe (2008)

4. Bishop, C.M., Svensén, M.: Bayesian hierarchical mixtures of experts. In: Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence, pp. 57–64 (2003)

5. Bloch, I.: Information Fusion in Signal and Image Processing: Major Probabilistic and Non-Probabilistic Numerical Approaches. John Wiley & Sons Inc., Chichester (2008)

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