Typed Cartesian Genetic Programming for Image Classification

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  title =        "Typed Cartesian Genetic Programming for Image
  author =       "Phil T. Cattani and Colin G. Johnson",
  booktitle =    "UK workshop on Computational Intelligence",
  year =         "2009",
  address =      "Nottingham",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.cs.kent.ac.uk/pubs/2009/2971/content.pdf",
  abstract =     "This paper introduces an extension to Cartesian
                 Genetic Programming (CGP), aimed at image
                 classification problems. Individuals in the population
                 consist of two layers of functions: image processing
                 functions, and traditional mathematical functions.
                 Information can be passed between these layers, and the
                 final result can either be an image or a numerical
                 value. This has been applied to image classification,
                 by using CGP to evolve image processing algorithms for
                 feature extraction. This paper presents results which
                 show that these automatically extracted features can
                 substantially increase classification accuracy on a
                 medical problem concerned with the analysis of
                 potentially cancerous cells.",
  notes =        "UKCI 2009 website gone",

Genetic Programming entries for Philip T Cattani Colin G Johnson