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		<isbn>978-85-7669-272-0</isbn>
		<citationkey>BorgesOrrFish:1994:RaBaFu</citationkey>
		<title>A radial basis function neural network for parts identification of three dimensional shapes</title>
		<format>Impresso, On-line.</format>
		<year>1994</year>
		<numberoffiles>1</numberoffiles>
		<size>5229 KiB</size>
		<author>Borges, Díbio Leandro,</author>
		<author>Orr, Mark J.,</author>
		<author>Fisher, Robert B.,</author>
		<affiliation>Department of Artificial Intelligence of Edinburgh University</affiliation>
		<affiliation>Centre for Cognitive Science of Edinburgh University</affiliation>
		<affiliation>Centre for Cognitive Science of Edinburgh University</affiliation>
		<editor>Freitas, Carla dal Sasso,</editor>
		<editor>Geus, Klaus de,</editor>
		<editor>Scheer, Sérgio,</editor>
		<e-mailaddress>cintiagraziele.silva@gmail.com</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 7 (SIBGRAPI)</conferencename>
		<conferencelocation>Curitiba</conferencelocation>
		<date>9 - 11 nov. 1994</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<volume>1</volume>
		<pages>77-84</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigo</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>function neural, function neural, image understanding.</keywords>
		<abstract>This discrimination of volumetric pieces or parts of objects from range data is one key element for achieving 3-D object recognition. In this paper it is shown that previously segmented and acquired super quadrics from range data can be reliably mapped into a set of qualitative volumetric shapes (geons) by means of an RBF (Radial Basis Function) neural network classifier. We use a regularized RBF classifier and the results are shown to be both reliable and efficient in the context of range image understanding.</abstract>
		<type>Visão Computacional</type>
		<language>en</language>
		<targetfile>11 A radial basis function neural network.pdf</targetfile>
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