Genetic Programming for Automatic Generation of Image Processing Algorithms on the CNN Neuroprocessing Architecture

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{conf/caepia/PreciadoPM03,
  title =        "Genetic Programming for Automatic Generation of Image
                 Processing Algorithms on the {CNN} Neuroprocessing
                 Architecture",
  author =       "Victor M. Preciado and Miguel A. Preciado and 
                 Miguel A. {Jaramillo Moran}",
  publisher =    "Springer",
  year =         "2003",
  volume =       "3040",
  editor =       "Ricardo Conejo and Maite Urretavizcaya and 
                 Jos{\'e}-Luis P{\'e}rez-de-la-Cruz",
  pages =        "374--383",
  series =       "Lecture Notes in Computer Science",
  booktitle =    "Current Topics in Artificial Intelligence 10th
                 Conference of the Spanish Association for Artificial
                 Intelligence, CAEPIA 2003, and 5th Conference on
                 Technology Transfer, TTIA 2003. Revised Selected
                 Papers",
  address =      "San Sebastian, Spain",
  month =        nov # " 12-14",
  keywords =     "genetic algorithms, genetic programming",
  bibdate =      "2004-07-08",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/caepia/caepia2003.html#PreciadoPM03",
  ISBN =         "3-540-22218-9",
  DOI =          "doi:10.1007/b98369",
  size =         "10 pages",
  abstract =     "The Cellular Neural Network Universal Machine (CNN-UM)
                 is a novel neuroprocessor algorithmically programmable
                 having real time and supercomputer power implemented in
                 a single VLSI chip. The local CNN connectivity provides
                 an useful computation paradigm when the problem can be
                 reformulated as a well-defined task where the signal
                 values are placed on a regular 2-D grid (i.e., image
                 processing), and the direct interaction between signal
                 values are limited within a local neighbourhood. This
                 paper introduces a Genetic Programming technique to
                 evolve both the structure and parameters of visual
                 algorithms on this architecture. This is accomplished
                 by defining a set of node functions and terminals to
                 implement the basic operations commonly used. Lastly,
                 the procedures involved in the use of the algorithm are
                 illustrated by several applications.",
}

Genetic Programming entries for Victor M Preciado Miguel A Preciado Miguel Angel Jaramillo Moran

Citations