On Evolution of Multi-Category Pattern Classifiers Suitable for Embedded Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{vasicek:2014:EuroGP,

• author = "Zdenek Vasicek and Michal Bidlo",
• title = "On Evolution of Multi-Category Pattern Classifiers Suitable for Embedded Systems",
• booktitle = "17th European Conference on Genetic Programming",
• year = "2014",
• editor = "Miguel Nicolau and Krzysztof Krawiec and Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and Juan J. Merelo and Victor M. {Rivas Santos} and Kevin Sim",
• series = "LNCS",
• volume = "8599",
• publisher = "Springer",
• pages = "234--245",
• address = "Granada, Spain",
• month = "23-25 " # apr,
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming :poster",
• isbn13 = "978-3-662-44302-6",
• DOI = "doi:10.1007/978-3-662-44303-3_20",
• abstract = "This paper addresses the problem of evolutionary design of classifiers for the recognition of handwritten digit symbols by means of Cartesian Genetic Programming. Two different design scenarios are investigated: the design of multiple-output classifier, and design of multiple binary classifiers. The goal is to evolve classification algorithms that employ substantially smaller amount of operations in contrast with conventional approaches such as Support Vector Machines. Even if the evolved classifiers do not reach the accuracy of the tuned SVM classifier, it will be shown that the accuracy is higher than 93percent and the number of required operations is a magnitude lower.",
• notes = "Part of \cite{Nicolau:2014:GP} EuroGP'2014 held in conjunction with EvoCOP2014, EvoBIO2014, EvoMusArt2014 and EvoApplications2014",

}

Genetic Programming entries for Zdenek Vasicek Michal Bidlo

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