Multiple Network CGP for the Classification of Mammograms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Publication details

Title of host publicationAPPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS
DatePublished - 2009
Pages405-413
Number of pages9
PublisherSPRINGER-VERLAG BERLIN
Place of PublicationBERLIN
EditorsM Giacobini, A Brabazon, S Cagnoni, GA DiCaro, A Ekart, AI EsparciaAlcazar, M Farooq, A Fink, P Machado, J McCormack, M ONeill, F Neri, M Preuss, F Rothlauf, E Tarantino, S Yang
Volume5484 LNCS
Original languageEnglish
ISBN (Print)978-3-642-01128-3

Abstract

This paper presents a novel representation of Cartesian genetic programming (CGP) in which multiple networks are used in the classification of high resolution X-rays of the breast, known as mammograms. CGP networks are used in a number of different recombination strategies and results are presented for mammograms taken from the Lawrence Livermore National Laboratory database.

    Research areas

  • Evolutionary algorithms, Cartesian genetic programming, mammography, MICROCALCIFICATIONS

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