Loopy belief propagation and probabilistic image processing

Tanaka, K., Inoue, J. and Titterington, M. (2003) Loopy belief propagation and probabilistic image processing. In: Adali, T., Larsen, J., van Hulle, M., Douglas, S. and Rouat, J. (eds.) 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (NNSP'03): Toulouse, France, 17-19 September, 2003. IEEE: Piscataway, N.J., USA, pp. 329-338. ISBN 9780780381773

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Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method. The algorithms are substantially equivalent to generalized loopy belief propagation.

Item Type:Book Sections
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Glasgow Author(s) Enlighten ID:Titterington, Professor D
Authors: Tanaka, K., Inoue, J., and Titterington, M.
Subjects:Q Science > QA Mathematics
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Copyright Holders:Copyright © 2003 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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