Genetic Programming for Image Recognition: An LGP Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{zhang:evows07,

• author = "Mengjie Zhang and Christopher Graeme Fogelberg",
• title = "Genetic Programming for Image Recognition: An LGP Approach",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP}, {EvoInteraction}, {EvoMUSART}, {EvoSTOC}, {EvoTransLog}",
• 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

Citations