An effective approach for detecting human torso from photo images
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: 2014شناسه الکترونیک: 10.1109/ICInfA.2014.6932699
کلیدواژه(گان): Gabor filters,face recognition,principal component analysis,support vector machines,LDA,OLPP-based Gabor feature dimensionality reduction,PCA,SVM,computational memory,facial expression recognition,high dimensional feature processing,linear discriminant analysis,orthogonal locality preserving projections,principle component analysis,support vector machines,Databases,Face recognition,Feature extraction,Gabor filters,Manifolds,Principal component analysis,Training,Demensionali
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An effective approach for detecting human torso from photo images
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contributor author | Mathew, M.M. , Salim, S. | |
date accessioned | 2020-03-12T20:49:30Z | |
date available | 2020-03-12T20:49:30Z | |
date issued | 2014 | |
identifier other | 6908257.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1026829?locale-attribute=fa | |
format | general | |
language | English | |
publisher | IEEE | |
title | An effective approach for detecting human torso from photo images | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8151897 | |
subject keywords | Gabor filters | |
subject keywords | face recognition | |
subject keywords | principal component analysis | |
subject keywords | support vector machines | |
subject keywords | LDA | |
subject keywords | OLPP-based Gabor feature dimensionality reduction | |
subject keywords | PCA | |
subject keywords | SVM | |
subject keywords | computational memory | |
subject keywords | facial expression recognition | |
subject keywords | high dimensional feature processing | |
subject keywords | linear discriminant analysis | |
subject keywords | orthogonal locality preserving projections | |
subject keywords | principle component analysis | |
subject keywords | support vector machines | |
subject keywords | Databases | |
subject keywords | Face recognition | |
subject keywords | Feature extraction | |
subject keywords | Gabor filters | |
subject keywords | Manifolds | |
subject keywords | Principal component analysis | |
subject keywords | Training | |
subject keywords | Demensionali | |
identifier doi | 10.1109/ICInfA.2014.6932699 | |
journal title | merging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD), 2014 Annual International Con | |
filesize | 279250 | |
citations | 0 |