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Title |
A Unicode based Deep Handwritten Character Recognition model for Telugu to English Language Translation |
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Author |
BV Subba Rao, J. Nageswara Rao, Bandi Vamsi, Venkata Nagaraju Thatha, Katta Subba Rao |
| Citation |
Vol. 24 No. 2 pp. 101-112 |
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Abstract |
Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine.. s. |
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Keywords |
Handwritten Character Recognition (HCR), Telugu Unicode’s, Language Translation, ML optimizers |
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