Paper Title:
Handwritten Digit Recognition Based-on Bernoulli Mixtures
  Abstract

A method based on Bernoulli mixtures is presented in this paper for the purpose of describing the pattern of probability distribution for each of the data sets of handwritten numerals (0-9), and then classifiers are formed from these. The test samples are recognized by their posterior probabilities conditioned on every classifier. Experimental results show that our method is superior to conventional methods on robustness and accuracy.

  Info
Periodical
Advanced Materials Research (Volumes 317-319)
Chapter
Machine Vision
Edited by
Xin Chen
Pages
901-904
DOI
10.4028/www.scientific.net/AMR.317-319.901
Citation
Z. H. Zhao, X. H. Hao, "Handwritten Digit Recognition Based-on Bernoulli Mixtures", Advanced Materials Research, Vols. 317-319, pp. 901-904, 2011
Online since
August 2011
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Price
$32.00
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