Optical Recognition of Handwritten by Aiding Computer Vision and Deep Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-57460-3_13
Reference13 articles.
1. N. Sneha, M. Sundaram, N. Preetham, Deep learning based application in identifying originality of the hand written document using convolution neural network, in Proceedings of the 2022 International Conference on Connected Systems and Intelligence (CSI), pp. 1–8 (2022). https://doi.org/10.1109/CSI54720.2022.9924050
2. D. Chauhan, D. Verma, A. Aggarwal, Hand-written characters recognition using siamese network design, in Proceedings of the 2022 1st International Conference on Informatics (ICI), pp. 66–70 (2022). https://doi.org/10.1109/ICI53355.2022.9786908
3. Y. Yin, W. Zhang, S. Hong, J. Yang, J. Xiong, G. Gui, Deep learning-aided OCR techniques for Chinese uppercase characters in the application of internet of things. IEEE Access 7, 47043–47049 (2019). https://doi.org/10.1109/ACCESS.2019.2909401
4. S.M. Darwish, K.O. Elzoghaly, An enhanced offline printed Arabic OCR model based on bio-inspired fuzzy classifier. IEEE Access 8, 117770–117781 (2020). https://doi.org/10.1109/ACCESS.2020.3004286
5. S. Kowsalya, P.S. Periasamy, Recognition of Tamil handwritten character using modified neural network with aid of elephant herding optimization. Multimedia Tools Appl. 78(17), 25043–25061 (2019)
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