Texture Analysis by Genetic Programming

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

  title =        "Texture Analysis by Genetic Programming",
  author =       "Andy Song and Vic Ciesielski",
  pages =        "2092--2099",
  booktitle =    "Proceedings of the 2004 IEEE Congress on Evolutionary
  year =         "2004",
  publisher =    "IEEE Press",
  month =        "20-23 " # jun,
  address =      "Portland, Oregon",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Real-world
  URL =          "http://goanna.cs.rmit.edu.au/~vc/papers/cec04-song.pdf",
  DOI =          "doi:10.1109/CEC.2004.1331154",
  abstract =     "This paper presents the use of genetic programming
                 (GP) to a complex domain, texture analysis. Two major
                 tasks of texture analysis, texture classification and
                 texture segmentation, are studied. Bitmap textures are
                 used in this investigation. In classification tasks,
                 the results show that GP is able to evolve accurate
                 classifiers based on texture features. Moreover by
                 using the presented method, GP is able to evolve
                 accurate classifiers without extracting texture
                 features. In texture segmentation tasks, the
                 investigation shows that a fast and accurate
                 segmentation method can be developed based on GP
                 generated texture classifiers.",
  notes =        "CEC 2004 - A joint meeting of the IEEE, the EPS, and
                 the IEE.",

Genetic Programming entries for Andy Song Victor Ciesielski