Detection of asphyxia from infant cry by linear kernel support vector machine enhanced with features from orthogonal least square

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Detection of asphyxia from infant cry by linear kernel support vector machine enhanced with features from orthogonal least square

An investigation into the performance of SVM with linear kernel and features ranked by OLS, to discriminate infants with asphyxia from their cries, is presented in this paper. The features of the cry signal were first transformed into MFC coefficients. The input feature set was then used for classif...

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Bibliographic Details
Published in:	ICCAIE 2011 - 2011 IEEE Conference on Computer Applications and Industrial Electronics
Main Author:	Sahak R.; Lee Y.K.; Mansor W.; Zabidi A.; Yassin A.I.M.
Format:	Conference paper
Language:	English
Published:	2011
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863341940&doi=10.1109%2fICCAIE.2011.6162157&partnerID=40&md5=cb68fa87f59a70f73c4556f8e6fceecb

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