Universidad Complutense de Madrid
E-Prints Complutense

Accuracy measures for fuzzy classification in remote sensing

Impacto

Downloads

Downloads per month over past year



Gómez, D. and Montero, Javier and Biging, Greg (2006) Accuracy measures for fuzzy classification in remote sensing. In IPMU 2006 : Information Processing and Management of Uncertainty in Knowledge-Based Systems : proceedings : Eleventh International Conference, Paris, Les Cordeliers, July 2-7, 2006. EDK, Paris, pp. 1556-1563. ISBN 2-84254-112-X

[img]
Preview
PDF
128kB

Official URL: http://www.math.s.chiba-u.ac.jp/~yasuda/open2all/Paris06/IPMU2006/HTML/FINALPAPERS/P608.PDF



Abstract

Over the last decades, many fuzzy classification algorithms have been proposed for image classification,and in particular to classify those images obtained by remote sensing.
But relatively little effort has been done to evaluate goodness or effectiveness of such algorithms. Such a problem is most of the times solved by means of a subjective evaluation, meanwhile in the crisp case quality
evaluation can be based upon an error matrix, in which the reference data set (the expert classi-fication) and crisp classifiers data set are been compared using specific
accuracy measures. In this paper,some of these measures are translated into the fuzzy case, so that more general accuracy measures between fuzzy classifiers and the reference data set can be considered.


Item Type:Book Section
Additional Information:

International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (11ª. 2006. París)

Uncontrolled Keywords:Accuracy assessment; Remote sensing; Fuzzy classification.
Subjects:Sciences > Computer science > Artificial intelligence
ID Code:29106
Deposited On:09 Mar 2015 12:24
Last Modified:18 Apr 2016 17:00

Origin of downloads

Repository Staff Only: item control page