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Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms
Conference proceeding

Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms

T.D. Pham and H. Yan
1997 Annual Meeting of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.97TH8297), pp.257-262
1997
DOI: https://doi.org/10.1109/NAFIPS.1997.624047

Abstract

Australia Boundary conditions Computer vision Density measurement Event detection Fuzzy sets Genetic algorithms Genetic engineering Image analysis Robots
Fuzzy and genetic algorithms are used to develop an approach for fusioning multiple handwritten numeral classifiers. A computational scheme of the Choquet (fuzzy) integral serves as a data fusion tool, whereas genetic algorithms are implemented to optimize the derivation of fuzzy densities which play a very important role for the calculation of fuzzy measures and fuzzy integrals. Several experimental results are provided to illustrate the effectiveness of this methodology.

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