The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving
  • Editorial Board

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Computing Conference 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Handwritten Digit Recognition based on Output-Independent Multi-Layer Perceptrons

Author 1: Ismail M. Keshta

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080604

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: With handwritten digit recognition being an established and significant problem that is facing computer vision and pattern recognition, there has been a great deal of research work that has been undertaken in this area. It is not a trivial task because of the big variation that exists in the writing styles that have been found in the available data. Therefore both, the features and the classifier need to be efficient. The core contribution of this research is the development of a new classification technique that is based on the MLP, which can be identified in handwritten documents as the binary digits ‘0’ and ‘1’. This technique maps the different sets of various input data onto the MLP output neurons. An experimental evaluation of the technique’s performance is provided. This evaluation is based on the well-known ‘Pen-Based Recognition of Handwritten Digits’ dataset, which is comprised of a total of 250 handwriting samples that are taken from 44 writers. The results obtained are very promising for such an approach in accurate handwriting recognition.

Keywords: Handwritten digit recognition; Pattern classification; Neural network mode; Two-class classification; Accuracy; Binary data

Ismail M. Keshta, “Handwritten Digit Recognition based on Output-Independent Multi-Layer Perceptrons” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080604

@article{Keshta2017,
title = {Handwritten Digit Recognition based on Output-Independent Multi-Layer Perceptrons},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080604},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080604},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {Ismail M. Keshta}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2021

29-30 April 2021

  • Virtual

Computing Conference 2021

15-16 July 2021

  • London, United Kingdom

IntelliSys 2021

2-3 September 2021

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2021

28-29 October 2021

  • Vancouver, Canada
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© 2018 The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org