Handwritten Digit Recognition Based-on Bernoulli Mixtures

Abstract:

Article Preview

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)

Edited by:

Xin Chen

Pages:

901-904

DOI:

10.4028/www.scientific.net/AMR.317-319.901

Citation:

Z. H. Zhao and X. H. Hao, "Handwritten Digit Recognition Based-on Bernoulli Mixtures", Advanced Materials Research, Vols. 317-319, pp. 901-904, 2011

Online since:

August 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.