TY - JOUR ID - 78884 TI - A Deep Learning Based Analysis of the Big Five Personality Traits from Handwriting Samples Using Image Processing JO - Journal of Information Technology Management JA - JITM LA - en SN - AU - Elngar, Ahmed A. AU - Jain, Nikita AU - Sharma, Divyanshu AU - Negi, Himani AU - Trehan, Anuj AU - Srivastava, Akash AD - Assistant Prof., Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni Suef, 62511, Egypt. AD - Assistant Prof., Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, New Delhi, India. AD - Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, New Delhi, India. Y1 - 2020 PY - 2020 VL - 12 IS - Special Issue: Deep Learning for Visual Information Analytics and Management. SP - 3 EP - 35 KW - computer vision KW - Convolutional neural networks KW - Artificial Neural Networks KW - Machine learning KW - Big Five Personality Traits KW - handwriting KW - Graphology DO - 10.22059/jitm.2020.78884 N2 - Handwriting Analysis has been used for a very long time to analyze an individual’s suitability for a job, and is in recent times, gaining popularity as a valid means of a person’s evaluation. Extensive Research has been done in the field of determining the Personality Traits of a person through handwriting. We intend to analyze an individual’s personality by breaking it down into the Big Five Personality Traits using their handwriting samples. We present a dataset that links personality traits to the handwriting features. We then propose our algorithm - consisting of one ANN based model and PersonaNet, a CNN based model. The paper evaluates our algorithm’s performance with baseline machine learning models on our dataset. Testing our novel architecture on this dataset, we compare our algorithm based on various metrics, and show that our novel algorithm performs better than the baseline Machine Learning models. UR - https://jitm.ut.ac.ir/article_78884.html L1 - https://jitm.ut.ac.ir/article_78884_2959805560be5b0bf7a105aad7477728.pdf ER -