Abstract
This paper aims to explore the scope of these neural networks and apply them to try and recognize handwritten data which consists of Tamil characters written by various people and convert it to a computerized text document. Through our system we will be targeting one of the gaps in the currently available technology, which is to properly identify and distinguish the characters in ancient manuscripts.
Machine Learning will be used to train the system to recognize the fed data and convolutional neural networks will be used to make decisions on its own and by doing that, it improves the accuracy of the prediction. The application of this system extends to various fields such as history, archaeology, paleography, engineering etc.
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Ramya, J., Raj Kumar, G.K., Peniel, C.J. (2020). ‘Agaram’ – Web Application of Tamil Characters Using Convolutional Neural Networks and Machine Learning. In: Hemanth, D.J., Kumar, V.D.A., Malathi, S., Castillo, O., Patrut, B. (eds) Emerging Trends in Computing and Expert Technology. COMET 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-030-32150-5_65
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DOI: https://doi.org/10.1007/978-3-030-32150-5_65
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