Deep Learning-based Recognition of Devanagari Handwritten Characters

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Published: Jul 13, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i7s.7003
Keywords:
Deep learning, Devanagari characters, convolutional neural network, handwritten character recognition, adaptive gradient methods, Image processing, Computer vision

Main Article Content

Prashant Sopanrao Kolhe
Head of Department, Department of Electronics and Telecommunication Engineering, TPCT’S College of Engineering, Osmanabad, India

Abstract

Numerous techniques have been used over many years to study handwriting recognition. There are two methods for reading handwriting, one of which is online and the other offline. Image recognition is the main part of the handwriting recognition process. Image recognition gives careful consideration to the picture's dimensions, viewing angle, and image quality. Machine learning and deep learning techniques are the two areas of focus for developers looking to increase the intelligence of computers. A person may learn to perform a task by repeatedly exercising it until they recall how to do it. His brain's neurons begin to work automatically, enabling him to carry out the task he has quickly learned. This and deep learning are fairly similar. It uses a variety of neural network designs to address a range of problems. The convolution neural network (CNN) is a very effective technique for handwriting and picture detection.

Article Details

How to Cite
Kolhe, P. S. . (2023). Deep Learning-based Recognition of Devanagari Handwritten Characters . International Journal on Recent and Innovation Trends in Computing and Communication, 11(7s), 300–306. https://doi.org/10.17762/ijritcc.v11i7s.7003
Issue
Vol. 11 No. 7s (2023)
Section
Articles

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