An Automatic Tool to Design CNN-Um Programs

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@InProceedings{Pazienza:2007:ECCTD,

• author = "Giovanni Egidio Pazienza and Kristof Karacs and Xavier Vilasis-Cardona",
• title = "An Automatic Tool to Design CNN-Um Programs",
• booktitle = "European Conference on Circuit Theory and Design, ECCTD 2007",
• year = "2007",
• pages = "492--495",
• address = "Seville, Spain",
• month = aug,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, Analogic algorithms design, CNN-UM programs, Automatic design, Image processing, Algorithm design and analysis, Analog computers, Binary trees, Cellular neural networks, Computer networks, Genetics, Image processing, Turing machines, Vehicle detection, Vehicles, cellular neural nets, digital signal processing chips, image processing, neural chips, CNN-UM program, automatic tool, cellular neural network universal machine, genetic approach, image processing task",
• DOI = "doi:10.1109/ECCTD.2007.4529640",
• abstract = "Programs for the Cellular Neural Network - Universal Machine are usually designed explicitly, and there is no method to create them automatically. In this paper we present a tool, based on a genetic approach, capable of determining what CNN templates compose a CNN-UM program performing a given image processing task, and in which order they must be applied to the input. The effectiveness of our system is demonstrated experimentally on real-life problems, like the route number detection on public transport vehicles.",
• notes = "Paper ID 5290 http://www.epapers.org/ecctd2007/ESR/paper_details.php?PHPSESSID=c19bb9ba66bd6d226e6533143786425e&paper_id=5290",

}

Genetic Programming entries for Giovanni Egidio Pazienza Kristof Karacs Xavier Vilasis Cardona

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