Handwritten Gujarati Character Recognition Using Machine Learning and Deep Learning

Yogiraj Zala; Krishn Limbachiya; Ankit Sharma; Pooja Shah

doi:10.2991/978-94-6463-136-4_76

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Handwritten Gujarati Character Recognition Using Machine Learning and Deep Learning

Authors

Yogiraj Zala¹^{, *}, Krishn Limbachiya¹, Ankit Sharma¹, Pooja Shah²

¹Department of Electronics and Instrumentation Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

²Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India

^*Corresponding author. Email: 19bic071@nirmauni.ac.in

Corresponding Author

Yogiraj Zala

Available Online 1 May 2023.

DOI: 10.2991/978-94-6463-136-4_76 How to use a DOI?
Keywords: Handwritten Gujarati numerals; Numerals classification; Deep Learning; Machine Learning techniques
Abstract: Gujarati character recognition has always been a field of study in need of improved techniques to reach a satisfactory degree of accuracy. This study developed a technique for predicting handwritten Gujarati numerals using various feature extraction and classification techniques. Deep learning models, including MobileNet, DenseNet, and NasNetMobile, are components of the feature extraction technique. XGBoost, Random Forest, Logistic Regression, Naive Bayes, Stochastic Gradient Descent, Decision Tree, and K-Nearest Neighbor are some of the techniques used to classify Gujarati numerals. This study used over 14,000 images of Gujarati numerals for an experiment and found significant outcomes.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series: Advances in Computer Science Research
Publication Date: 1 May 2023
ISBN: 10.2991/978-94-6463-136-4_76
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-136-4_76 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Yogiraj Zala
AU  - Krishn Limbachiya
AU  - Ankit Sharma
AU  - Pooja Shah
PY  - 2023
DA  - 2023/05/01
TI  - Handwritten Gujarati Character Recognition Using Machine Learning and Deep Learning
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 863
EP  - 873
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_76
DO  - 10.2991/978-94-6463-136-4_76
ID  - Zala2023
ER  -

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