Using Loops in Genetic Programming for a Two Class Binary Image Classification Problem

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

@InProceedings{LiCie04,
  author =       "Xiang Li and Vic Ciesielski",
  title =        "Using Loops in Genetic Programming for a Two Class
                 Binary Image Classification Problem",
  booktitle =    "AI 2004: Advances in Artificial Intelligence:
                 Proceedings of the 17th Australian Joint Conference on
                 Artificial Intelligence",
  year =         "2004",
  editor =       "Geoffrey I. Webb and Xinghuo Yu",
  volume =       "3339",
  series =       "Lecture Notes in Computer Science",
  pages =        "898--909",
  address =      "Cairns, Australia",
  month =        dec # " 4-6",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, image
                 classification, classification problem",
  ISBN =         "3-540-24059-4",
  URL =          "http://www.springerlink.com/index/6MDEKV7A1821E0UY",
  DOI =          "doi:10.1007/b104336",
  abstract =     "Loops are rarely used in genetic programming (GP),
                 because they lead to massive computation due to the
                 increase in the size of the search space. We have
                 investigated the use of loops with restricted semantics
                 for a problem in which there are natural repetitive
                 elements, that of distinguishing two classes of images.
                 Using our formulation, programs with loops were
                 successfully evolved and performed much better than
                 programs without loops. Our results suggest that loops
                 can successfully used in genetic programming in
                 situations where domain knowledge is available to
                 provide some restrictions on loop semantics.",
}

Genetic Programming entries for Xiang Li Victor Ciesielski

Citations