Gender prediction based on the expiratory flow volume curve | IEEE Conference Publication | IEEE Xplore

Gender prediction based on the expiratory flow volume curve


Abstract:

This study is performed estimated using the gender of the person is the expiration of the current-volume curve obtained from the test. Gender studies estimate is carried ...Show More

Abstract:

This study is performed estimated using the gender of the person is the expiration of the current-volume curve obtained from the test. Gender studies estimate is carried out using two different machine learning method. These methods Gaussian Mixture Model (GMM) and Support Vector Machines are (SVM). Gender prediction in both methods are performed using classification. The proposed methods have three main stages. These stages are feature extraction, training and gender of test person is detected. Performance evaluation is made according to the experimental results obtained. As a result of these studies, the gender prediction accuracy of 99.43 per cent are carried out.
Date of Conference: 16-19 May 2015
Date Added to IEEE Xplore: 22 June 2015
Electronic ISBN:978-1-4673-7386-9
Print ISSN: 2165-0608
Conference Location: Malatya, Turkey

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