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dc.contributor.authorMuhammad Naufal, Mansor-
dc.contributor.authorSyahryull Hi-Fi Syam, Ahmad Jamil-
dc.contributor.authorAhmad Kadri, Junoh-
dc.contributor.authorMuhammad Nazri, Rejab-
dc.contributor.authorAddzrull Hi-Fi Syam, Ahmad Jamil-
dc.contributor.authorJamaluddin, Ahmad-
dc.date.accessioned2013-07-10T07:47:15Z-
dc.date.available2013-07-10T07:47:15Z-
dc.date.issued2012-07-03-
dc.identifier.citationp. 918-921en_US
dc.identifier.isbn978-146730478-8-
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6271350-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/26562-
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.orgen_US
dc.description.abstractwithin this paper, pain detection is exposed and reviewed for detecting facial changes of patient in a hospital in Neonatal Intensive Care Unit (NICU). The system propesed three stage. The first stage implements Haar Cascade detection to detect the infant face. Secondly, PCA was employed for feature extraction. The third module extracts the PCA features of faces by measuring certain dimensions of pain and no pain regions with Support Vector Machine classifier. From 300 samples of face images, it is found that the identification rate of reaches 93.18%.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Computer and Communication Engineering (ICCCE 2012)en_US
dc.subjectDetection of facial changesen_US
dc.subjectNICU patienten_US
dc.subjectSupport Vector Machine classifieren_US
dc.titleFast infant pain detection methoden_US
dc.typeWorking Paperen_US
dc.contributor.urlapairia@yahoo.comen_US
dc.contributor.urlsyahrull30@yahoo.comen_US
dc.contributor.urlkadri@unimap.edu.myen_US
dc.contributor.urlnazri_554@yahoo.comen_US
dc.contributor.urlazrulhifisyam@yahoo.comen_US
dc.contributor.urldrjamaluddin@pls.moh.gov.myen_US
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