Maximum Entropy and Gaussian Models for Image Object Recognition-Reference-Cited by-同舟云学术

Maximum Entropy and Gaussian Models for Image Object Recognition

Published:2002 Issue: Volume: Page:498-506
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Keysers Daniel,Och Franz Josef,Ney Hermann

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45783-6_60

Reference15 articles.

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2. J. Dahmen, D. Keysers, H. Ney, M.O. Güld: Statistical Image Object Recognition using Mixture Densities. J. Mathematical Imaging and Vision, 14(3):285–296, May 2001.

3. J. Dahmen, R. Schlüter, H. Ney: Discriminative Training of Gaussian Mixture Densities for Image Object Recognition. In 21. DAGM Symposium Mustererkennung, Bonn, Germany, pp. 205–212, September 1999.

4. J.N. Darroch, D. Ratcliff: Generalized Iterative Scaling for Log-Linear Models. Annals of Mathematical Statistics, 43(5):1470–1480, 1972.

5. T. Jaakkola, M. Meila, T. Jebara: Maximum Entropy Discrimination. In Advances in Neural Information Processing Systems 12, MIT Press, Cambridge, MA, pp. 470–476, 2000.

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