Handwritten digit recognition using MNIST dataset is a major project made with the help of Neural Network. It basically detects the scanned images of handwritten digits. We have taken this a step ...

The central aspect of this paper is to discuss the deep learning concept ideas and problems faced during training the model and come with a solution for better accuracy, illustrated by digit ...

To rescue us from all this complexity comes neural network, making machines learn and resolve all those complexities for us, scaling out with each level of complexity. One of such complex problem is ...

Handwritten character recognition is one of the classical problems ... Improved generalization of the neural network is achieved through the use of data augmentation. • The label propagation allows ...

This project is a handwritten digit recognition system implemented using a Neural Network. The goal is to train the model to accurately classify and recognize handwritten digits (0-9) from input ...

In this paper, we introduce the Convolutional Neural Network (CNN) based on TensorFlow framework is introduced, and use the MINIST data set which is widely used in handwritten digit recognition to ...