Mars Terrain Image Classification using Cartesian Genetic Programming

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

  author =       "J. Leitner and S. Harding and A. Forster and 
                 J. Schmidhuber",
  title =        "Mars Terrain Image Classification using Cartesian
                 Genetic Programming",
  booktitle =    "11th International Symposium on Artificial
                 Intelligence, Robotics and Automation in Space
  year =         "2012",
  address =      "Turin, Italy",
  month =        "4-6 " # sep,
  organisation = "European Space Agency",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming",
  URL =          "",
  size =         "8 pages",
  abstract =     "Automatically classifying terrain such as rocks, sand
                 and gravel from images is a challenging machine vision
                 problem. In addition to human designed approaches, a
                 great deal of progress has been made using machine
                 learning techniques to perform classification from
                 images. In this work, we demonstrate the first known
                 use of Cartesian Genetic Programming (CGP) to this

                 Our CGP for Image Processing (CGP-IP) system quickly
                 learns classifiers and detectors for certain terrain
                 types. The learnt program outperforms currently used
                 techniques for classification tasks performed on a
                 panorama image collected by the Mars Exploration Rover
  date-added =   "2012-05-28 16:31:09 +0200",
  date-modified = "2012-05-28 16:31:09 +0200",
  notes =        "fitness = MCC, classify rocks, sand and gravel from

Genetic Programming entries for Juergen Leitner Simon Harding Alexander Forster Jurgen Schmidhuber