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Persons’ Personality Traits Recognition using Machine Learning Algorithms and Image Processing Techniques

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dc.contributor.author Fernando, T.G.I.
dc.contributor.author Nilmini, K.S.
dc.date.accessioned 2017-09-29T05:29:46Z
dc.date.available 2017-09-29T05:29:46Z
dc.date.issued 2016
dc.identifier.citation T.G.I. Fernando, K.S. Nilmini, (2016), “Persons’ Personality Traits Recognition using Machine Learning Algorithms and Image Processing Techniques”, ACSIJ Advances in Computer Science: an International Journal, Vol. 5, Iss: 1 en_US, si_LK
dc.identifier.issn 23225157
dc.identifier.uri http://dr.lib.sjp.ac.lk/handle/123456789/5582
dc.description.abstract The context of this work is the development of persons’ personality recognition system using machine learning techniques. Identifying the personality traits from a face image are helpful in many situations, such as identification of criminal behavior in criminology, students’ learning attitudes in education sector and recruiting employees. Identifying the personality traits from a face image has rarely been studied. In this research identifying the personality traits from a face image includes three separate methods; ANN, SVM and deep learning. Face area of an image is identified by a color segmentation algorithm. Then that extracted image is input to personality recognition process. Features of the face are identified manually and input them to ANN and SVM. Each personality trait is valued from 1 to 9. In the second attempt m- SVM is used because outputs are multi-valued. ANN gave better results than m-SVM. In the third attempt we propose a methodology to identify personality traits using deep learning. en_US, si_LK
dc.language.iso en_US en_US, si_LK
dc.subject Artificial Neural Networks (ANN) en_US, si_LK
dc.subject Support Vector Machine (SVM) en_US, si_LK
dc.subject Multi Valued Multi Class Support Vector Machine (m-SVM) en_US, si_LK
dc.subject Deep learning en_US, si_LK
dc.subject Personality trait en_US, si_LK
dc.title Persons’ Personality Traits Recognition using Machine Learning Algorithms and Image Processing Techniques en_US, si_LK
dc.type Article en_US, si_LK


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