(Enter summary)
Abstract: We compare two classifier approaches, namely classifiers
based on Multi Layer Perceptrons (MLPs) and Gaussian Mixture Models
(GMMs), for use in a face verification system. The comparison is carried
out in terms of performance, robustness and practicability. Apart from
structural di#erences, the two approaches use di#erent training criteria;
the MLP approach uses a discriminative criterion, while the GMM approach
uses a combination of Maximum Likelihood (ML) and Maximum
a Posteriori (MAP) ... (Update)
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BibTeX entry: (Update)
F. Cardinaux, C. Sanderson and S. Marcel, "Comparison of MLP and GMM Classifiers for Face Verification on XM2VTS", IDIAP-RR 03-10, Martigny, Switzerland, 2003. http://citeseer.ist.psu.edu/cardinaux03comparison.html More
@misc{ cardinaux03comparison,
author = "F. Cardinaux and C. Sanderson and S. Marcel",
title = "Comparison of MLP and GMM Classifiers for Face Verification on XM2VTS",
text = "F. Cardinaux, C. Sanderson and S. Marcel, Comparison of MLP and GMM Classifiers
for Face Verification on XM2VTS, IDIAP-RR 03-10, Martigny, Switzerland,
2003.",
year = "2003",
url = "citeseer.ist.psu.edu/cardinaux03comparison.html" }
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