Deep Learning based English Handwritten Character Recognition

Somil Gupta, Tanvi Bansal, Manish Kumar Sharma

Abstract: In this paper we propose a convolutional neural network based handwritten character recognition using SVM as an end classifier. The learning model is based on CNN (Convolutional Neural Network) which is used as a feature extraction tool. The proposed method is more efficient than other existing methods and will be more efficient than modifying the CNN with complex architecture. The recognition rate achieved by the proposed method is 93.3 % which is greater than other existing methods. The computation time of training phase is 13.14 sec and that of testing phase is 13.27 sec. The proposed system was validated by 6 validation points. The overall accuracy of system is 93 %

Keywords: Deep Learning, Convolutional Neural Network, Handwriting recognition, SVM

How to Cite?: Somil Gupta, Tanvi Bansal, Manish Kumar Sharma, "Deep Learning based English Handwritten Character Recognition", Volume 7 Issue 4, April 2018, International Journal of Science and Research (IJSR), Pages: 1402-1404, https://www.ijsr.net/getabstract.php?paperid=ART20181693, DOI: https://dx.doi.org/10.21275/ART20181693