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Comparison of ANN and SVM to identify children handwriting difficulties

Hasseim, Anith Adibah and Sudirman, Rubita and Khalid, Puspa Inayat and Mashadi, Narges Tabatabaey (2013) Comparison of ANN and SVM to identify children handwriting difficulties. Journal of Engineering, 5 . pp. 1-5. ISSN 1947-3931

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Official URL: http://dx.doi.org/10.4236/eng.2013.55B001

Abstract

This paper compares two classification methods to determine pupils who have difficulties in writing. Classification ex-periments are made with neural network and support vector machine method separately. The samples are divided into two groups of writers, below average printers (test group) and above average printers (control group) are applied. The aim of this paper is to demonstrate that neural network and support vector machine can be successfully used in classi-fying pupils with or without handwriting difficulties. Our results showed that support vector machine classifier yield slightly better percentage than neural network classifier and it has a much stable result.

Item Type:Article
Uncontrolled Keywords:neural network, support vector machine, handwriting difficulties
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:40376
Deposited By: Narimah Nawil
Deposited On:19 Aug 2014 01:48
Last Modified:05 Mar 2019 01:47

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