Recognition of Handwritten Digit using Convolutional Neural Network (CNN)
Recognition of Handwritten Digit using Convolutional Neural Network (CNN)
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Keywords

convolutional neural network; MNIST dataset; MatConvNet; ReLu; softmax

How to Cite

Md. Anwar Hossain, & Md. Mohon Ali. (2019). Recognition of Handwritten Digit using Convolutional Neural Network (CNN). Global Journal of Computer Science and Technology, 19(D2), 27–33. Retrieved from https://gjcst.com/index.php/gjcst/article/view/474

Abstract

Humans can see and visually sense the world around them by using their eyes and brains Computer vision works on enabling computers to see and process images in the same way that human vision does Several algorithms developed in the area of computer vision to recognize images The goal of our work will be to create a model that will be able to identify and determine the handwritten digit from its image with better accuracy We aim to complete this by using the concepts of Convolutional Neural Network and MNIST dataset We will also show how MatConvNet can be used to implement our model with CPU training as well as less training time Though the goal is to create a model which can recognize the digits we can extend it for letters and then a person s handwriting Through this work we aim to learn and practically apply the concepts of Convolutional Neural Networks
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