ARCHIVES
Original Article
AI-Based OCR System for Handwritten Medical Prescription Recognition and Interpretation
Shaik Sharjeel1
Mohammad Ubaidulla Arif2
1Student, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India. 2Assistant Professor, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India.
Published Online: May-August 2025
Pages: 365-370
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250402050
References
1. R. Smith, “An overview of the Tesseract OCR engine,” Proceedings of the Ninth International Conference on Document Analysis and Recognition, vol. 2, pp. 629–633, 2007. doi: 10.1109/ICDAR.2007.4376991.
2. A. Graves and J. Schmidhuber, “Offline handwriting recognition with multidimensional recurrent neural networks,” Advances in Neural Information Processing Systems, vol. 21, pp. 545–552, 2009.
3. I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. MIT Press, 2016. [Online]. Available: http://www.deeplearningbook.org
4. R. Kaur and K. Kaur, “A comprehensive study of handwritten character recognition using deep learning,” Procedia Computer Science, vol. 167, pp. 292–301, 2019. doi: 10.1016/j.procs.2020.03.223.
5. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE, vol. 86, no. 11, pp. 2278–2324, 1998. doi: 10.1109/5.726791.
6. P. Rajpurkar et al., “SQuAD: 100,000+ Questions for Machine Comprehension of Text,” arXiv preprint arXiv:1606.05250, 2016. [Online]. Available: https://arxiv.org/abs/1606.05250
7. T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient estimation of word representations in vector space,” arXiv preprint arXiv:1301.3781, 2013. [Online]. Available: https://arxiv.org/abs/1301.3781
8. A. Vaswani et al., “Attention is all you need,” Advances in Neural Information Processing Systems, vol. 30, pp. 5998–6008, 2017.
9. J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805, 2018. [Online]. Available: https://arxiv.org/abs/1810.04805
10. N. Kumar and R. Rani, “A hybrid deep learning model for improving performance of medical OCR,” Journal of King Saud University – Computer and Information Sciences, 2020. doi: 10.1016/j.jksuci.2020.10.001.
2. A. Graves and J. Schmidhuber, “Offline handwriting recognition with multidimensional recurrent neural networks,” Advances in Neural Information Processing Systems, vol. 21, pp. 545–552, 2009.
3. I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. MIT Press, 2016. [Online]. Available: http://www.deeplearningbook.org
4. R. Kaur and K. Kaur, “A comprehensive study of handwritten character recognition using deep learning,” Procedia Computer Science, vol. 167, pp. 292–301, 2019. doi: 10.1016/j.procs.2020.03.223.
5. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE, vol. 86, no. 11, pp. 2278–2324, 1998. doi: 10.1109/5.726791.
6. P. Rajpurkar et al., “SQuAD: 100,000+ Questions for Machine Comprehension of Text,” arXiv preprint arXiv:1606.05250, 2016. [Online]. Available: https://arxiv.org/abs/1606.05250
7. T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient estimation of word representations in vector space,” arXiv preprint arXiv:1301.3781, 2013. [Online]. Available: https://arxiv.org/abs/1301.3781
8. A. Vaswani et al., “Attention is all you need,” Advances in Neural Information Processing Systems, vol. 30, pp. 5998–6008, 2017.
9. J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805, 2018. [Online]. Available: https://arxiv.org/abs/1810.04805
10. N. Kumar and R. Rani, “A hybrid deep learning model for improving performance of medical OCR,” Journal of King Saud University – Computer and Information Sciences, 2020. doi: 10.1016/j.jksuci.2020.10.001.
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