Efficient recognition of Bangla handwritten digits based on deep neural network

ISSN: 22773878
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Nw-a-days world has started to move into machine based technologies. Recognition of various features, shapes, images etc., has become extremely excited topics over recent years. Many authors proposed various techniques to recognition of handwritten digits on different languages. This paper presents a new technique based on deep neural network for the purpose of efficiently recognition of handwritten digits for Bangla language. Two datasets are used in this paper including CMATERDB 3.1.1 dataset and ISI (Indian Statistical Institute) dataset. About 24500 samples are used for training purpose and 4800 samples are used for testing purpose and the proposed technique achieves 98.70 percent accuracy. This paper also presents detailed overview on artificial neurons, and deep neural network. In addition, the efficiency of proposed method shown by comparing the results with other existing techniques.




Rahman, M. L., Jahan, I., Saha, A., & Yousuf Ali, M. N. (2018). Efficient recognition of Bangla handwritten digits based on deep neural network. International Journal of Recent Technology and Engineering, 7(4), 200–203.

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