Krzysztof Krawiec


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"A genetic programming algorithm for synthesis of object detection systems is proposed and applied to the task of license plate recognition in uncontrolled lighting conditions. The method evolves solutions represented as data flows of high-level parametric image operators. In an extended variant

@INPROCEEDINGS { Krawiec:2013:EvoIASP-short,
    AUTHOR = { Krzysztof Krawiec and Mateusz Nawrocki },
    TITLE = { Implicit Fitness Sharing for Evolutionary Synthesis of License Plate Detectors },
    BOOKTITLE = { "Applications of Evolutionary Computing },
    YEAR = { 2013 },
    EDITOR = { Anna I. Esparcia-Alcazar et al. },
    VOLUME = { 7835 },
    SERIES = { Lecture Notes in Computer Science },
    PAGES = { 376--386 },
    ADDRESS = { "Vienna },
    PUBLISHER_ADDRESS = { Berlin },
    MONTH = { "3-5 " # apr },
    ORGANISATION = { EvoStar },
    PUBLISHER = { Springer },
    KEYWORDS = { "genetic algorithms },
    ISBN13 = { 978-3-642-37191-2 },
    DOI = { doi:10.1007/978-3-642-37192-9_38 },
    SIZE = { 11 pages },
    ABSTRACT = { "A genetic programming algorithm for synthesis of object detection systems is proposed and applied to the task of license plate recognition in uncontrolled lighting conditions. The method evolves solutions represented as data flows of high-level parametric image operators. In an extended variant },
    NOTES = { "http://www.kevinsim.co.uk/evostar2013/cfpEvoApplications.html EvoApplications2013 held in conjunction with EuroGP2013 },
}


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