Comparison of Evolving Uniform, Non-uniform Cellular Automaton, and Genetic Programming for Centroid Detection with Hardware Agents

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{conf/pact/KomannMF07,

• author = "Marcus Komann and Andreas Mainka and Dietmar Fey",
• title = "Comparison of Evolving Uniform, Non-uniform Cellular Automaton, and Genetic Programming for Centroid Detection with Hardware Agents",
• booktitle = "Proceedings of the 9th International Conference Parallel Computing Technologies, PaCT 2007",
• year = "2007",
• editor = "Victor E. Malyshkin",
• volume = "4671",
• series = "Lecture Notes in Computer Science",
• pages = "432--441",
• address = "Pereslavl-Zalessky, Russia",
• month = sep # " 3-7",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Cellular Automaton",
• isbn13 = "978-3-540-73939-5",
• DOI = "doi:10.1007/978-3-540-73940-1_43",
• size = "10 pages",
• abstract = "Current industrial applications require fast and robust image processing in systems with low size and power dissipation. One of the main tasks in industrial vision is fast detection of centroids of objects. This paper compares three different approaches for finding geometric algorithms for centroid detection which are appropriate for a fine-grained parallel hardware architecture in an embedded vision chip. The algorithms shall comprise emergent capabilities and high problem-specific functionality without requiring large amounts of states or memory. For that problem, we consider uniform and non-uniform cellular automata (CA) as well as Genetic Programming. Due to the inherent complexity of the problem, an evolutionary approach is applied. The appropriateness of these approaches for centroid detection is discussed.",
• bibdate = "2007-08-31",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/pact/pact2007.html#KomannMF07",

}

Genetic Programming entries for Marcus Komann Andreas Mainka Dietmar Fey

Citations