Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/53690
Type: Artigo de periódico
Title: A relevance feedback method based on genetic programming for classification of remote sensing images
Author: dos Santos, JA
Ferreira, CD
Torres, RD
Goncalves, MA
Lamparelli, RAC
Abstract: This paper presents an interactive technique for remote sensing image classification. In our proposal, users are able to interact with the classification system, indicating regions of interest (and those which are not). This feedback information is employed by a genetic programming approach to learning user preferences and combining image region descriptors that encode spectral and texture properties. Experiments demonstrate that the proposed method is effective for image classification tasks and outperforms the traditional MaxVer method. (C) 2010 Elsevier Inc. All rights reserved.
Subject: Content-based image retrieval
Region descriptors
Relevance feedback
Genetic programming
Remote sensing image classification
Country: EUA
Editor: Elsevier Science Inc
Rights: fechado
Identifier DOI: 10.1016/j.ins.2010.02.003
Date Issue: 2011
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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