References
- Popli, R., Kansal, I., Garg, A., Goyal, N., & Garg, K. (2021). Classification and recognition of online handwritten alphabets using machine learning methods. In IOP Conference Series: Materials Science and Engineering (Vol. 1022, No. 1, p. 012111). IOP Publishing.
- Frey, P. W., & Slate, D. J. (1991). Letter recognition using Holland-style adaptive classifiers. Machine learning, 6, 161-182.
- Ptucha, R., Such, F. P., Pillai, S., Brockler, F., Singh, V., & Hutkowski, P. (2019). Intelligent character recognition using fully convolutional neural networks. Pattern recognition, 88, 604-613.
- Vaidya, R., Trivedi, D., Satra, S., & Pimpale, M. (2018, April). Handwritten character recognition using deep-learning. In 2018 second international conference on inventive communication and computational technologies (ICICCT) (pp. 772-775). IEEE.
- de Campos, T. E., Babu, B. R., & Varma, M. (2009, February). Character recognition in natural images. In International conference on computer vision theory and applications (Vol. 1, pp. 273-280). SCITEPRESS.
- Singh, A., & Bist, A. S. (2019). A wide scale survey on handwritten character recognition using machine learning. Int J Comput Sci Eng, 7(6), 124-134.
- Islam, M. A., & Iacob, I. E. (2023). Manuscripts Character Recognition Using Machine Learning and Deep Learning. Modelling, 4(2), 168-188.
- Somashekar, T. (2021). A survey on handwritten character recognition using deep learning technique. Journal of University of Shanghai for Science and Technology, 23(6).
- Reddy, R. V. K., & Babu, U. R. (2019). Handwritten hindi character recognition using deep learning techniques. Int J Comput Sci Eng.
- Singh, S. K., & Yadav, J. (2021, March). Machine learning & image processing for hand written digits and alphabets recognition from document image through MATLAB simulation. In IOP Conference Series: Materials Science and Engineering (Vol. 1084, No. 1, p. 012021). IOP Publishing.
- Sinha, A., Shahid, M., Nandan, A., Iwendi, C., Giri, A. K., & Anand, S. (2023, February). A Novel Approach of Machine Learning Application in Astrophysics: Morphological Feature Wrapping Based Ensemble Method for Galaxy Shape Classification Using GAMA Dataset. In International Conference on Advances in Communication Technology and Computer Engineering (pp. 593-603). Cham: Springer Nature Switzerland.