DIMENSIONALITY REDUCTION OF HYPERSPECTRAL SIGNATURES FOR OPTIMIZED DETECTION OF INVASIVE SPECIES

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" DIMENSIONALITY REDUCTION OF HYPERSPECTRAL SIGNATURES FOR OPTIMIZED DETECTION OF INVASIVE SPECIES "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	151909
Doc. No	:	ET23701
Main Entry	:	Abhinav Mathur
Title Proper	:	DIMENSIONALITY REDUCTION OF HYPERSPECTRAL SIGNATURES FOR OPTIMIZED DETECTION OF INVASIVE SPECIES
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	The aim of this thesis is to investigate the use of hyperspectral reflectance signals for the discrimination of cogongrass (Imperata cylindrica) from other subtly different vegetation species. Receiver operating characteristics (ROC) curves are used to determine which spectral bands should be considered as candidate features. Multivariate statistical analysis is then applied to the candidate features to determine the optimum subset of spectral bands. Linear discriminant analysis (LDA) is used to compute the optimum linear combination of the selected subset to be used as a feature for classification. Similarly, for comparison purposes, ROC analysis, multivariate statistical.............-....,....-...,..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	:	TL46952.pdf
Title and statement of responsibility and	:	DIMENSIONALITY REDUCTION OF HYPERSPECTRAL SIGNATURES FOR OPTIMIZED DETECTION OF INVASIVE SPECIES [Thesis]