RT Journal Article
T1 Spectral Fuzzy Classification: A Supervised Approach
A1 Del Amo, Ana
A1 Gómez González, Daniel
A1 Montero De Juan, Francisco Javier
AB The goal of this paper is to present an 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.
PB European Society for Fuzzy Logic and Technology
SN 1134-5632
YR 2008
FD 2008
LK https://hdl.handle.net/20.500.14352/51323
UL https://hdl.handle.net/20.500.14352/51323
LA eng
NO Gobierno de España
DS Docta Complutense
RD 10 abr 2025