Rate the Article: Handwritten English Character Recognition Using Logistic Regression and Neural Network, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 130 | Views: 400 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper | Computer Science & Engineering | India | Volume 5 Issue 6, June 2016 | Rating: 6.9 / 10


Handwritten English Character Recognition Using Logistic Regression and Neural Network

Tapan Kumar Hazra, Rajdeep Sarkar, Ankit Kumar


Abstract: Hand written character recognition is a challenging task often resulting in ambiguous labels. Using the concepts of Machine Learning we have tried to develop an Optical Character Recognition (OCR) system where an algorithm is trained on a data set of known letters and then can learn to accurately classify new data. Our optical character recognition (OCR) system for handwritten English characters comprises of two steps-Generating training set data using an OCR tool and then Applying different machine learning algorithm on the training set and start the learning process. A variety of algorithms have shown good accuracy for the handwritten letters, two of which are looked here.


Keywords: neural network, classification, optical character recognition, regularization, logistic regression


Edition: Volume 5 Issue 6, June 2016,


Pages: 750 - 754



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