Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/341495
Type: Artigo
Title: A soft computing framework for image classification based on recurrence plots
Author: Menini, Nathalia
Almeida, Alexandre E.
Lamparelli, Rubens
le Maire, Guerric
dos Santos, Jefersson A.
Pedrini, Helio
Hirota, Marina
Torres, Ricardo da S.
Abstract: Suitable time series representations play an important role in classification tasks. In this letter, we investigate the use of recurrence-plot-(RP)-based representations in the classification of eucalyptus regions in remote sensing images. The proposed framework is composed of three steps. First, time series associated with image pixels are represented by RP images; next, RP images are characterized by means of visual description approaches; finally, we use a soft computing framework based on genetic programing to discover an effective combination of time series dissimilarity functions to combine extracted features. Performed experiments in a eucalyptus classification problem demonstrated that the proposed framework is effective when compared to approaches based on the use of time series itself
Subject: Eucalipto
Country: Estados Unidos
Editor: Institute of Electrical and Electronics Engineers
Rights: Fechado
Identifier DOI: 10.1109/LGRS.2018.2872132
Address: https://ieeexplore.ieee.org/document/8500137
Date Issue: 2019
Appears in Collections:IC - Artigos e Outros Documentos

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