Comparison of ANN and SVM to Identify Children Handwriting Difficulties

Anith Adibah Hasseim, Rubita Sudirman, Puspa Inayat Khalid, Narges Tabatabaey-Mashadi

Research output: Contribution to journalBook/Film/Article reviewpeer-review

Abstract

This paper compares two classification methods to determine pupils who have difficulties in writing. Classification experiments 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 classifying 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.
Original languageEnglish
Number of pages5
JournalEngineering
Volume5
Publication statusPublished - May 2013

Keywords

  • Neural Network
  • Support Vector Machine
  • Handwriting Difficulties

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