Journal ArticleDOI
Methods of combining multiple classifiers and their applications to handwriting recognition
Lei Xu,Adam Krzyżak,Ching Y. Suen +2 more
- Vol. 22, Iss: 3, pp 418-435
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TLDR
On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly.Abstract:
Possible solutions to the problem of combining classifiers can be divided into three categories according to the levels of information available from the various classifiers. Four approaches based on different methodologies are proposed for solving this problem. One is suitable for combining individual classifiers such as Bayesian, k-nearest-neighbor, and various distance classifiers. The other three could be used for combining any kind of individual classifiers. On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly. For example, on the US zipcode database, 98.9% recognition with 0.90% substitution and 0.2% rejection can be obtained, as well as high reliability with 95% recognition, 0% substitution, and 5% rejection. >read more
Citations
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Journal ArticleDOI
Fusion of neural networks with fuzzy logic and genetic algorithm
TL;DR: A hybrid synergistic method of fuzzy logic and genetic algorithm to optimally combine neural networks is proposed and the experimental results show that the performance could be improved significantly with the proposed softcomputing techniques.
Journal ArticleDOI
Algorithm of designing compound recognition system on the basis of combining classifiers with simultaneous splitting feature space into competence areas
Konrad Jackowski,Michal Wozniak +1 more
TL;DR: The paper presents the novel adaptive splitting and selection algorithm (AdaSS) used for learning compound pattern recognition system and the results of experiments for algorithm evaluation purposes prove the quality of the proposed approach.
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