Abstract
The objective of this study is to create a Handwritten English Alphabet Recognition System, emphasizing signature recognition. In a global context where handwritten records and signatures play pivotal roles in various sectors, including legal, finance, and authentication, the demand for accurate and efficient recognition methods is paramount. This research project endeavors to construct a resilient system that can precisely identify and categorize handwritten English letters and signatures through the application of machine learning techniques, notably deep learning. The system employs convolutional and recurrent neural networks to adapt to diverse writing styles and varying levels of complexity.
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Kumar, R., Patra, S., Singh, A.P. (2024). Handwritten English Alphabets Recognition System. In: Garg, D., Rodrigues, J.J.P.C., Gupta, S.K., Cheng, X., Sarao, P., Patel, G.S. (eds) Advanced Computing. IACC 2023. Communications in Computer and Information Science, vol 2053. Springer, Cham. https://doi.org/10.1007/978-3-031-56700-1_24
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DOI: https://doi.org/10.1007/978-3-031-56700-1_24
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