International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

An Effective Deep Learning Approach For Handwritten Ol-Chiki Character Recognition

Author(s) Sumanta Daw, Dr. Abhoy Chand Mondal
Country India
Abstract In this paper, we propose a deep convolution neural network approach to recognize Ol-Chiki handwritten characters. Here we describe recognition of handwritten basic characters of Ol-Chiki script, used by more than 10 million tribal people in India mostly from Assam, Bengal, Bihar, Odisha and Jharkhand. There are 30 basic characters and 10 numeral digits in Ol-Chiki. We have used a dataset of 10000 handwritten isolated character samples written by 100 persons. Convolution Neural Network (CNN) architecture has been used for the recognition of handwritten isolated Ol-Chiki characters. Our system has been tested on Ol-Chiki isolated dataset and we have achieved 92% accuracy on almost on all Ol-Chiki characters.
Keywords Convolution Neural Network, Deep Learning, Ol-Chiki
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-18
Cite This An Effective Deep Learning Approach For Handwritten Ol-Chiki Character Recognition - Sumanta Daw, Dr. Abhoy Chand Mondal - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.17473
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.17473
Short DOI https://doi.org/gtvt4n

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