A modular eigen subspace scheme for high-dimensional data classification

NCUIR > Research Center > Center for Space and Remote Sensing Research > journal & Dissertation > Item 987654321/35941

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/35941

Title:	A modular eigen subspace scheme for high-dimensional data classification
Authors:	Chang,YL;Han,CC;Jou,FD;Fan,KC;Chen,KS;Chang,JH
Contributors:	太空及遙測研究中心
Keywords:	HYPERSPECTRAL DATA;STACK FILTERS
Date:	2004
Issue Date:	2010-07-07 15:54:27 (UTC+8)
Publisher:	中央大學
Abstract:	In this paper, a novel filter-based greedy modular subspace (GMS) technique is proposed to improve the accuracy of high-dimensional data classification. The proposed approach initially divides the whole set of high-dimensional features into several arbitr
Relation:	FUTURE GENERATION COMPUTER SYSTEMS
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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