Digit Recognition using TensorFlow Tool

K. V. N. Rajesh*, K.V.N. Ramesh**, M. Hymavathi ***, K. Syam Sundar Reddy****
* HOD, Department of Electronics and Computer Engineering, Vignan's Institute of Information Technology, Visakhapatnam, India.
** Technical Architect, Tech Mahindra, Visakhapatnam, India.
***-**** UG Scholar, Department of Information Technology, Vignan's Institute of Information Technology, Visakhapatnam, India.
Periodicity:September - November'2017
DOI : https://doi.org/10.26634/jpr.4.3.13887

Abstract

Deep learning and Neural Network algorithms are a branch of Machine learning that can automatically identify patterns in the data, and then use the uncovered patterns to predict future data, or to perform other alternative kinds of decision making under unreliability. Neural Networks is a method of computing, which is based on a collection of large number of neural units, which acts as a biological brain and solve problems with large clusters of biological neurons connected by axons. Deep Learning algorithms are used to model high level abstractions in data. Digit Recognition is a combination of Deep Learning and Neural Network algorithms, which uses TensorFlow tool as an interface to develop a model. This paper describes the recognition of handwritten scanned digits by a system and displays the output as digital numbers by using Machine Learning methods with the help of TensorFlow tool.

Keywords

Digit Recognition, TensorFlow, Neural Networks, Deep Learning, Machine Learning

How to Cite this Article?

Rajesh, K. V. N., Ramesh, K. V. N., Hymavathi, M., and Reddy, K. S. S. (2017). Digit Recognition using TensorFlow Tool. i-manager’s Journal on Pattern Recognition, 4(3), 27-31. https://doi.org/10.26634/jpr.4.3.13887

References

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