Image classification and processing using modified parallel-ACTIT

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

  author =       "Jun Ando and Tomoharu Nagao",
  title =        "Image classification and processing using modified
  booktitle =    "IEEE International Conference on Systems, Man and
                 Cybernetics, SMC 2009",
  year =         "2009",
  month =        oct,
  pages =        "1787--1791",
  keywords =     "genetic algorithms, genetic programming, automatic
                 construction of tree-structural image transformation,
                 image classification, image recognition, modified
                 parallel-ACTIT, training image sets, image
                 classification, tree data structures",
  DOI =          "doi:10.1109/ICSMC.2009.5346894",
  ISSN =         "1062-922X",
  abstract =     "Image processing and recognition technologies are
                 required to solve various problems. We have already
                 proposed the system which automatically constructs
                 image processing with Genetic Programming (GP),
                 Automatic Construction of Tree-structural Image
                 Transformation (ACTIT). However, it is necessary that
                 training image sets are properly classified in advance
                 if they have various characteristics. In this paper, we
                 propose Modified Parallel-ACTIT which automatically
                 classifies training image sets into several
                 subpopulations. And it optimizes tree-structural image
                 transformation for each training image sets in each
                 subpopulations. We show experimentally that Modified
                 Parallel-ACTIT is more effective in comparison with
                 ordinary ACTIT.",
  notes =        "Also known as \cite{5346894}",

Genetic Programming entries for Jun Ando Tomoharu Nagao