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		<citationkey>SouzaCost:2007:NaCoTe</citationkey>
		<author>Souza, Jackson Gomes de,</author>
		<author>Costa, José Alfredo F.,</author>
		<affiliation>Federal University of Rio Grande do Norte - Electrical Engineering Dept.</affiliation>
		<affiliation>Federal University of Rio Grande do Norte - Electrical Engineering Dept.</affiliation>
		<title>Natural Computing Techniques for Data Clustering and Image Segmentation</title>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)</conferencename>
		<year>2007</year>
		<editor>Gonçalves, Luiz,</editor>
		<editor>Wu, Shin Ting,</editor>
		<booktitle>Proceedings</booktitle>
		<date>Oct. 7-10, 2007</date>
		<publisheraddress>Porto Alegre</publisheraddress>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<conferencelocation>Belo Horizonte</conferencelocation>
		<keywords>Pattern Recognition, Image Segmentation, Medical Imaging and Visualization, Applications, Natural Computing, Genetic Algorithms.</keywords>
		<abstract>This paper presents innovative ways to solve data clustering and image segmentation using Natural computing, a novel approach to solve real life problems inspired in the life. Evolutionary Computing, which is based on the concepts of the evolutionary biology and individual-to-population adaptation, and Swarm Intelligence, which is inspired in the behavior of individuals that, in group, try to achieve better results for a complex optimization problem, are detailed and very experimental results present a comparison between algorithms' implementations.</abstract>
		<language>en</language>
		<tertiarytype>Technical Poster</tertiarytype>
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