A method of combining multiple experts for the recognition ofunconstrained handwritten numerals
Huang, Y.S.
Suen, C.Y.
Centre for Pattern Recognition and Machine Intelligence, Concordia Univ., Montreal, Que.;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1995
Volume: 17,
Issue: 1
On page(s): 90-94
ISSN: 0162-8828
References Cited: 12
CODEN: ITPIDJ
INSPEC Accession Number: 4871860
Digital Object Identifier: 10.1109/34.368145
Current Version Published: 2002-08-06
Abstract
For pattern recognition, when a single classifier cannot provide a
decision which is 100 percent correct, multiple classifiers should be
able to achieve higher accuracy. This is because group decisions are
generally better than any individual's. Based on this concept, a method
called the “Behavior-Knowledge Space Method” was developed,
which can aggregate the decisions obtained from individual classifiers
and derive the best final decisions from the statistical point of view.
Experiments on 46451 samples of unconstrained handwritten numerals have
shown that this method achieves very promising performances and
outperforms voting, Bayesian, and Dempster-Shafer approaches
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