Genetic Programming for Image Recognition: An LGP Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Mengjie Zhang and Christopher Graeme Fogelberg",
  title =        "Genetic Programming for Image Recognition: An LGP
  booktitle =    "Applications of Evolutionary Computing,
                 EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP},
                 {EvoInteraction}, {EvoMUSART}, {EvoSTOC},
  year =         "2007",
  month =        "11-13 " # apr,
  editor =       "Mario Giacobini and Anthony Brabazon and 
                 Stefano Cagnoni and Gianni A. {Di Caro} and Rolf Drechsler and 
                 Muddassar Farooq and Andreas Fink and 
                 Evelyne Lutton and Penousal Machado and Stefan Minner and 
                 Michael O'Neill and Juan Romero and Franz Rothlauf and 
                 Giovanni Squillero and Hideyuki Takagi and A. Sima Uyar and 
                 Shengxiang Yang",
  series =       "LNCS",
  volume =       "4448",
  publisher =    "Springer Verlag",
  address =      "Valencia, Spain",
  pages =        "340--350",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-71804-8",
  DOI =          "doi:10.1007/978-3-540-71805-5_37",
  abstract =     "This paper describes a linear genetic programming
                 approach to multi-class image recognition problems. A
                 new fitness function is introduced to approximate the
                 true feature space. The results show that this approach
                 outperforms the basic tree based genetic programming
                 approach on all the tasks investigated here and that
                 the programs evolved by this approach are easier to
                 interpret. The investigation on the extra registers and
                 program length results in heuristic guidelines for
                 initially setting system parameters.",
  notes =        "EvoWorkshops2007",

Genetic Programming entries for Mengjie Zhang Christopher Fogelberg