Implementation of the Unsupervised Possibility Fuuy C-Means Algorithm for Classification of Hyper Spectral Data

منو

" Implementation of the Unsupervised Possibility Fuuy C-Means Algorithm for Classification of Hyper Spectral Data "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	150491
Doc. No	:	ET22283
Main Entry	:	Fernando Gallo Plasencia
Title Proper	:	Implementation of the Unsupervised Possibility Fuuy C-Means Algorithm for Classification of Hyper Spectral Data
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	This research presents the implementation of the UnsupervisedPossibility Fuzzy C-Means algorithm for classification of Hyperspectral Data.The research is divided in two experiments: The first experiment used threedifferent synthetic data sets. A comparison between the Unsupervised PossibilityFuzzy C-Means and the Unsupervised Fuzzy C-Means algorithms is done foreach synthetic data set. The main objective of this comparison is to see theeffectiveness of the implemented method in the estimation of the means whenoutliers are presented in the data set. The second experiment was run onremotely sensed data and the results are presented for comparison purposes.-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL45489.pdf
Title and statement of responsibility and	:	Implementation of the Unsupervised Possibility Fuuy C-Means Algorithm for Classification of Hyper Spectral Data [Thesis]