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dc.contributor.authorPayungsak Kasemsumranen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.description.abstract© 2016 IEEE. A string grammar fuzzy K-nearest neighbor is developed by incorporating 2 types of membership value into string grammar K-nearest neighbor. We apply these two string grammar fuzzy K-nearest neighbors in the face recognition system. The system provides 99.25%, 99.75%, 79.57%, 93.85%, and 100% in ORL, MIT-CBCL, Georgia Tech, FEI and JAFFE databases, respectively. Although, the results are satisfied, there are some limitations on the system. It is not scale-invariant. Also, the Levenshtein distance might create misperception between strings that are actually far apart but the calculated distance is small.en_US
dc.subjectComputer Scienceen_US
dc.subjectSocial Sciencesen_US
dc.titleFace recognition using string grammar fuzzy K-nearest neighboren_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2016 8th International Conference on Knowledge and Smart Technology, KST 2016en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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