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Handwritten Character Recognition using Neural Networks: A study of Various Feature Based Classification Techniques

Author(s):

Shreya Girdhar , Maharaja Agrasen Institute Of Technology; Sachin Gupta, Maharaja Agrasen Institute Of Technology; Bhaskar Kapoor, Maharaja Agrasen Institute Of Technology

Keywords:

Character Recognition, Artificial Neural Network, Supervised Learning, Back Propagation Algorithm

Abstract

Neural network is a machine designed to work the way in which the brain performs a particular task. Character recognition techniques recognize the characters written on a paper documents and convert it in digital form. Character recognition is gaining importance due to its application in various fields. Handwritten character recognition is a difficult due to variation of writing style, different size of writing and shape of the character by different people. Accuracy and efficiency are the major parameters to be achieved in the field of handwritten character recognition. Neural network is the technique used to improve the accuracy and efficiency of the system. This paper contains a detailed review of Handwritten Character Recognition using Neural Network by back propagation algorithm.

Other Details

Paper ID: IJSRDV6I11061
Published in: Volume : 6, Issue : 1
Publication Date: 01/04/2018
Page(s): 2163-2165

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