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		<doi>10.1109/SIBGRA.2002.1167129</doi>
		<citationkey>MartinsGuimFons:2002:TeFeNe</citationkey>
		<title>Texture feature neural classifier for remote sensing image retrieval systems</title>
		<year>2002</year>
		<numberoffiles>1</numberoffiles>
		<size>863 KiB</size>
		<author>Martins, Mauricio Pozzobon,</author>
		<author>Guimaraes, Lamartine N. Frutuoso,</author>
		<author>Fonseca, Leila Maria Garcia,</author>
		<editor>Gonçalves, Luiz Marcos Garcia,</editor>
		<editor>Musse, Soraia Raupp,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Giraldi, Gilson,</editor>
		<editor>Dreux, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI)</conferencename>
		<conferencelocation>Fortaleza, CE, Brazil</conferencelocation>
		<date>10-10 Oct. 2002</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<abstract>Texture information is useful for image data browsing and retrieval. The goal of this paper is to present a texture classification system for remote sensing images addressed to the administration of great collections of those images. The proposed classifier is a hybrid system composed by an unsupervised neural network and a supervised one. Starting from a small portion of the image (pattern) the system should recognize the most similar class to the pattern in a database as well as to identify the images that contain similar patterns. The texture feature vectors used to characterize the patterns are obtained from the images processed by a bank of Gabor Filters. Some experimental results using textures of the Brodatz album, multi-spectral and radar images have presented here.</abstract>
		<language>en</language>
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		<notes>The conference was held in Fortaleza, CE, Brazil, from October 7 to 10.</notes>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/10.24.10.41</url>
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