• M.Ragini
• B.Hima Bindu
• Y.Lakshmi Sai
• K.M.M.M.Sai
• B.Gayatri Sruthi

Handwritten digit Recognition is the process of identifying the handwritten digits from papers, images and letters and photographs by a computer. The computer will receive the input and interpret the handwritten digits using machine learning. The digit recognition has been an interesting topic of analysis for years. The areas of analysis include processing of checks, interpretation of address on envelopes. This can also used for identifying the input from smart phones, tablets using a finger. They are many classification techniques developed using the machine learning for identification. Techniques like k-nearest neighbors algorithm and SVM classifiers model are used. These techniques are having low accuracy which is not sufficient for real time applications. In order to improve the efficiency and accuracy deep learning can be used. Deep learning is a tool developed recently for image processing, object detecting and also for recognition of handwritten characters and digits .Many machine learning tools have been developed for deep learning such as Google's Tensorflow, Keras, Theano and scikitlearn which make the applications more accurate and efficient.

"Handwritten Digit Recognizer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.356-359, March-2019, Available :http://www.jetir.org/papers/JETIR1903B55.pdf

"Handwritten Digit Recognizer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp356-359, March-2019, Available at : http://www.jetir.org/papers/JETIR1903B55.pdf