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An Empirical Study of Dimensionality Reduction Methods for Biometric Recognition

contributor authorKerdprasop, Nittaya
contributor authorChanklan, Ratiporn
contributor authorHirunyawanakul, Anusara
contributor authorKerdprasop, Kittisak
date accessioned2020-03-12T22:46:33Z
date available2020-03-12T22:46:33Z
date issued2014
identifier other7023278.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1094156?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleAn Empirical Study of Dimensionality Reduction Methods for Biometric Recognition
typeConference Paper
contenttypeMetadata Only
identifier padid8233832
subject keywordsgraphics processing units
subject keywordsn motion estimation
subject keywordsn parallel algorithms
subject keywordsn video coding
subject keywordsn CTU-based parallel processing
subject keywordsn FME
subject keywordsn GPU
subject keywordsn HEVC
subject keywordsn IME
subject keywordsn coding efficiency loss
subject keywordsn exhausted motion estimation
subject keywordsn fractional motion estimation
subject keywordsn integer motion estimation
subject keywordsn multistep composite method
subject keywordsn real time encoding
subject keywordsn redundancies elimiation
subject keywordsn variable block sizes
subject keywordsn Encoding
subject keywordsn Graphics processing units
subject keywordsn Instruction sets
subject keywordsn Interpolation
subject keywordsn Motion e
identifier doi10.1109/ICCE-TW.2014.6904012
journal titleecurity Technology (SecTech), 2014 7th International Conference on
filesize284419
citations0


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