Face recognition using string grammar fuzzy K-nearest neighbor

© 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...

Full description

Saved in:

Bibliographic Details
Main Authors:	Payungsak Kasemsumran, Sansanee Auephanwiriyakul, Nipon Theera-Umpon
Format:	Conference Proceeding
Published:	2018
Subjects:	Computer Science Medicine Social Sciences
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84966534385&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55525
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University

id	th-cmuir.6653943832-55525
record_format	dspace
spelling	th-cmuir.6653943832-555252018-09-05T03:14:54Z Face recognition using string grammar fuzzy K-nearest neighbor Payungsak Kasemsumran Sansanee Auephanwiriyakul Nipon Theera-Umpon Computer Science Medicine Social Sciences © 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. 2018-09-05T02:57:34Z 2018-09-05T02:57:34Z 2016-03-23 Conference Proceeding 2-s2.0-84966534385 10.1109/KST.2016.7440531 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84966534385&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55525
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Computer Science Medicine Social Sciences
spellingShingle	Computer Science Medicine Social Sciences Payungsak Kasemsumran Sansanee Auephanwiriyakul Nipon Theera-Umpon Face recognition using string grammar fuzzy K-nearest neighbor
description	© 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.
format	Conference Proceeding
author	Payungsak Kasemsumran Sansanee Auephanwiriyakul Nipon Theera-Umpon
author_facet	Payungsak Kasemsumran Sansanee Auephanwiriyakul Nipon Theera-Umpon
author_sort	Payungsak Kasemsumran
title	Face recognition using string grammar fuzzy K-nearest neighbor
title_short	Face recognition using string grammar fuzzy K-nearest neighbor
title_full	Face recognition using string grammar fuzzy K-nearest neighbor
title_fullStr	Face recognition using string grammar fuzzy K-nearest neighbor
title_full_unstemmed	Face recognition using string grammar fuzzy K-nearest neighbor
title_sort	face recognition using string grammar fuzzy k-nearest neighbor
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84966534385&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55525
_version_	1681424521984212992

Face recognition using string grammar fuzzy K-nearest neighbor

Similar Items