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International Journal of New Technology and Research

Impact Factor 3.953

(An ISO 9001:2008 Certified Online Journal)
India | Germany | France | Japan

Handwriting Recognition using LSTM Networks

( Volume 4 Issue 3,March 2018 ) OPEN ACCESS

Sarita Yadav, Ankur Pandey, Pulkit Aggarwal, Rachit Garg, Vishal Aggarwal


Recognizing digits in an optimal way is a challenging problem. Recent deep learning based approaches have achieved great success on handwriting recognition. English characters are among the most widely adopted writing systems in the world. This paper presents a comparative evaluation of the standard LSTM RNN model with other deep models on MNIST dataset.

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