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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151157
Doc. No : ET22949
Main Entry : Srilatha Panchanathan
Title Proper : ANOMALY DETECTION IN HYPERSPECTRAL SIGNATURES USING AUTOMATED DEWATWE SPECTROSCOPY METHODS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The goal of this research was to detect anomalies in remotely sensed Hyperspectralimages using automated derivative based methods. A database of Hyperspectralsignatures was used that had simulated additive Gaussian anomalies that modeled aweakly concentrated aerosol in several spectral bands. The automated pattern detectionsystem was carried out in four steps. They were 1r feature extraction, 2n feature reductionthrough linear discriminant analysis, 3l performance characterization through receiveroperating characteristic curves and 4i signature classification using nearest mean andmaximum likelihood classifiers. The Hyperspectral database contained signatures with...,....-...,..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 : TL46177.pdf
Title and statement of responsibility and : ANOMALY DETECTION IN HYPERSPECTRAL SIGNATURES USING AUTOMATED DEWATWE SPECTROSCOPY METHODS [Thesis]
 
 
 
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