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An effective method of 3D facial features segmentation

Author:
Li, Yuan
,
Guo, Zhe
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/VLHCC.2014.6883022
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/1079698
Keyword(s): data analysis,n decision trees,n neural nets,n regression analysis,n support vector machines,n data processing,n data scientists,n decision trees,n exploratory data analysis,n exploratory data modelling,n linear regression,n neural networks,n programming languages,n spreadsheet-based interaction technique,n statistical modelling,n statistical tools,n support vector machines,n teach-and-try technique,n Biological system modeling,n Computati
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    An effective method of 3D facial features segmentation

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contributor authorLi, Yuan
contributor authorGuo, Zhe
date accessioned2020-03-12T22:20:34Z
date available2020-03-12T22:20:34Z
date issued2014
identifier other7003809.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1079698?locale-attribute=en
formatgeneral
languageEnglish
publisherIEEE
titleAn effective method of 3D facial features segmentation
typeConference Paper
contenttypeMetadata Only
identifier padid8216054
subject keywordsdata analysis
subject keywordsn decision trees
subject keywordsn neural nets
subject keywordsn regression analysis
subject keywordsn support vector machines
subject keywordsn data processing
subject keywordsn data scientists
subject keywordsn decision trees
subject keywordsn exploratory data analysis
subject keywordsn exploratory data modelling
subject keywordsn linear regression
subject keywordsn neural networks
subject keywordsn programming languages
subject keywordsn spreadsheet-based interaction technique
subject keywordsn statistical modelling
subject keywordsn statistical tools
subject keywordsn support vector machines
subject keywordsn teach-and-try technique
subject keywordsn Biological system modeling
subject keywordsn Computati
identifier doi10.1109/VLHCC.2014.6883022
journal titlemage and Signal Processing (CISP), 2014 7th International Congress on
filesize1026299
citations0
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