This paper is published in Volume-7, Issue-4, 2021
Area
Machine Learning
Author
Sanjeeva Kumar, Seenakula Ravi Shankar, Shashank M. V., Vandana K. C., Farhana Kausar
Org/Univ
Atria Institute of Technology, Bangalore, Karnataka, India
Pub. Date
02 July, 2021
Paper ID
V7I4-1140
Publisher
Keywords
Deep learning, Convolution neural network, Artificial neural network

Citationsacebook

IEEE
Sanjeeva Kumar, Seenakula Ravi Shankar, Shashank M. V., Vandana K. C., Farhana Kausar. Handwritten Digit Recognition using Deep Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sanjeeva Kumar, Seenakula Ravi Shankar, Shashank M. V., Vandana K. C., Farhana Kausar (2021). Handwritten Digit Recognition using Deep Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Sanjeeva Kumar, Seenakula Ravi Shankar, Shashank M. V., Vandana K. C., Farhana Kausar. "Handwritten Digit Recognition using Deep Learning." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

Deep learning is powerful technique in current generation. This Paper presents the results of handwritten digit recognition on well-known image database using Convolution neural network. Deep learning increases accuracy and reduces computation time as was caused by simple artificial neural network. The applications of digit recognition includes in postal mail sorting, bank check processing, form data entry, etc. The heart of problem lies within the ability to develop an efficient algorithm that can recognize hand written digits and which is submitted by users by the way of a scanner, tablet, and other digital devices. The main objective of this paper is to ensure effective and reliable approaches for recognition of handwritten digits.