CNN Based Handwritten Devanagari Digits Recognition
|Gaurav Kumar1 , Sachin Kumar2|
1 Dept. of Computer Science and Engineering, NIT, Warangal, India.
2 Dept. of Computer Science and Engineering, MIT AOE, Pune, India.
|Correspondence should be addressed to: firstname.lastname@example.org.|
Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-7 , Page no. 71-74, Jul-2017
Online published on Jul 30, 2017
Copyright © Gaurav Kumar, Sachin Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Gaurav Kumar, Sachin Kumar, “CNN Based Handwritten Devanagari Digits Recognition”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.7, pp.71-74, 2017.
MLA Style Citation: Gaurav Kumar, Sachin Kumar "CNN Based Handwritten Devanagari Digits Recognition." International Journal of Computer Sciences and Engineering 5.7 (2017): 71-74.
APA Style Citation: Gaurav Kumar, Sachin Kumar, (2017). CNN Based Handwritten Devanagari Digits Recognition. International Journal of Computer Sciences and Engineering, 5(7), 71-74.
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|Handwritten Digit Recognition has huge demand in commercial, administrative and academic domains. In recent years lot of good work has been done to improve accuracy of Handwritten Digit Recognition System but accuracy of such systems depend on large datasets. Deep Convolutional Neural Network have shown superior results to traditional shallow net-works in many recognition task. In this paper, a convolutional neural network (CNN) based Devanagari digit recognition system is highlighted. The dataset contains 21969 hand written 28x28 size images. The result of proposed system showed 99.07% accuracy on our dataset.|
|Key-Words / Index Term :|
|Devanagri Digits, CNN, SVM, KNN, CUDA, GPU,Tensorflow|
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