Spectral fuzzy classification system: a supervised approach.

Título original	Spectral fuzzy classification system: a supervised approach.
Título inglés	Spectral fuzzy classification system: a supervised approach.
Título español	Sistema de clasificación difusa espectral: versión supervisada.
Autor/es	Del Amo, Ana ; Gómez, Daniel ; Montero, Javier
Organización	Smiths Aerosp. Electr. Syst., Grand Rapids (Michigan), Estados Unidos;Dep. Estad. I.O. Univ. Complut. Madrid, Madrid, España
Revista	1134-5632
Publicación	2003, 10 (2-3): 141-154, 15 Ref.
Tipo de documento	articulo
Idioma	Inglés
Resumen inglés	The goal of this paper is to present all algorithm for pattern recognition, leveraging on an existing fuzzy clustering algorithm developed by Del Amo et al. [3, 5], and modifying it to its supervised version, in order to apply the algorithm to different pattern recognition applications in Remote Sensing. The main goal is to recognize the object and stop the search depending on the precision of the application. The referred algorithm was the core of a classification system based on Fuzzy Sets Theory (see [14]), approaching remotely sensed classification problems as multicriteria decision making problems, solved by means of an outranking methodology (see [12] and also [11]). The referred algorithm was a unsupervised classification algorithm, but now in this paper will present a modification of the original algorithm into a supervised version.
Clasificación UNESCO	110208
Palabras clave español	Lógica difusa ; Reconocimiento de formas ; Algoritmos de clasificación ; Teledetección
Código MathReviews	MR2052478
Código Z-Math	1086.68582
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