On Evolution of Multi-Category Pattern Classifiers Suitable for Embedded Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{vasicek:2014:EuroGP,
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author = "Zdenek Vasicek and Michal Bidlo",
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title = "On Evolution of Multi-Category Pattern Classifiers
Suitable for Embedded Systems",
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booktitle = "17th European Conference on Genetic Programming",
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year = "2014",
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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",
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series = "LNCS",
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volume = "8599",
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publisher = "Springer",
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pages = "234--245",
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address = "Granada, Spain",
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month = "23-25 " # apr,
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming :poster",
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isbn13 = "978-3-662-44302-6",
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DOI = "doi:10.1007/978-3-662-44303-3_20",
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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.",
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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
Citations