Handwritten Digit Recognition Application uses Deeplearning4j and Neural Networks to classify digits.
Deeplearning4j is an Open-Source, Distributed, Deep Learning Library for the Java Virtual Machine.
The Dataset used is MNIST Dataset. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image. The MNIST problem is a dataset developed by Yann LeCun, Corinna Cortes and Christopher Burges for evaluating machine learning models on the handwritten digit classification problem. Each image is a 28 by 28 pixel square (784 pixels total). A standard spit of the dataset is used to evaluate and compare model, where 60,000 images are used to train a model and a separate set of 10,000 images are used to test it.