15th International Conference on Pattern Recognition (ICPR'00) - Volume 2
Multivariate Structural Bernoulli Mixtures for Recognition of Handwritten Numerals
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
As shown recently, the structural optimization of probabilistic neural networks can be included into EM algorithm by introducing a special type of mixtures. The method has been applied to recognize unconstrained handwritten numerals from the database of Concordia University in Montreal. In the present paper, we discuss the possibility of a proper initialization of EM algorithm for estimating the class-conditional multivariate Bernoulli mixtures.
Citation:
Jirí Grim, Pavel Pudil, Petr Somol, "Multivariate Structural Bernoulli Mixtures for Recognition of Handwritten Numerals," icpr, vol. 2, pp.2585, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000