Resolution of the Inverse Problem for Iterated Function Systems using Evolutionary Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Sarafopoulos:2006:CEC,
  author =       "Anargyros Sarafopoulos and Bernard Buxton",
  title =        "Resolution of the Inverse Problem for Iterated
                 Function Systems using Evolutionary Algorithms",
  booktitle =    "Proceedings of the 2006 IEEE Congress on Evolutionary
                 Computation",
  year =         "2006",
  editor =       "Gary G. Yen and Lipo Wang and Piero Bonissone and 
                 Simon M. Lucas",
  pages =        "3816--3823",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9487-9",
  DOI =          "doi:10.1109/CEC.2006.1688428",
  size =         "8 pages",
  abstract =     "The resolution of the inverse problem for iterated
                 function systems (IFS) is a problem that has remained
                 open, currently there is no general solution that
                 requires no human interaction and provides optimal
                 results. Here we present a novel approach to the
                 resolution of the general inverse problem for IFS using
                 segmentation of target images in conjuction with an
                 Evolutionary Algorithm that is a Genetic Programming-
                 Evolutionary Strategies hybrid.",
  notes =        "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
                 the IEE.

                 IEEE Catalog Number: 06TH8846D",
}

Genetic Programming entries for Anargyros Sarafopoulos Bernard Buxton

Citations