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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