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dc.contributor.authorNopsuwanchai, Roongroj
dc.contributor.authorBiem, Alain
dc.contributor.authorClocksin, William
dc.identifier.citationNopsuwanchai , R , Biem , A & Clocksin , W 2006 , ' Maximization of mutual information for offline Thai handwriting recognition ' , IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 28 , no. 8 , pp. 1347-1351 .
dc.identifier.otherPURE: 500229
dc.identifier.otherPURE UUID: 97bf39db-279b-4d81-b3f7-fb9b358dd1f3
dc.identifier.otherScopus: 33748147868
dc.description.abstractThis paper aims to improve the performance of an HMM-based offline Thai handwriting recognition system through discriminative training and the use of fine-tuned feature extraction methods. The discriminative training is implemented by maximizing the mutual information between the data and their classes. The feature extraction is based on our proposed block-based PCA and composite images, shown to be better at discriminating Thai confusable characters. We demonstrate significant improvements in recognition accuracies compared to the classifiers that are not discriminatively optimizeden
dc.relation.ispartofIEEE Transactions on Pattern Analysis and Machine Intelligence
dc.titleMaximization of mutual information for offline Thai handwriting recognitionen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Engineering and Computer Science
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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