DocumentCode
2618499
Title
Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms
Author
Pham, Tuan D. ; Yan, Hong
Author_Institution
Fac. of Inf. Sci. & Eng., Univ. of Canberra, Belconnen, ACT, Australia
fYear
1997
fDate
21-24 Sep 1997
Firstpage
257
Lastpage
262
Abstract
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
Keywords
fuzzy set theory; genetic algorithms; handwriting recognition; integral equations; pattern classification; sensor fusion; Choquet fuzzy integral; computational scheme; data fusion tool; fuzzy algorithms; fuzzy densities; fuzzy measures; genetic algorithms; multiple handwritten numeral classifier fusion; Australia; Boundary conditions; Computer vision; Density measurement; Event detection; Fuzzy sets; Genetic algorithms; Genetic engineering; Image analysis; Robots;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location
Syracuse, NY
Print_ISBN
0-7803-4078-7
Type
conf
DOI
10.1109/NAFIPS.1997.624047
Filename
624047
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