Project Digit Recognition

I'm training a simple neural network to recognize handwritten digits. You can execute the program and draw your own digit. The network makes a prediction and tells you what digit you drew. I implemented a neural network with one hidden layer and a variable amount of input and output neurons. The network has an accuracy of 93.4% on the mnist test data, but the accuracy is lower with the GUI (will be fixed in the future).

Features

• GUI that promts the user to draw a digits on a canvas
• Data Loader that loads and handles the mnist data
• Network class which creates a neural network
• Matrix class with matrix calculations
• Graph class that creates graphs for the training process of the network (work in progress)
• Mnist training data is included

Technologies Used

• JavaFX + FXML
• Java language
• Mnist dataset
• Maven build automation tool
• VSCode editor

Getting Started

Prerequisites

• Java 8 or higher
• JavaFX
• Maven
• VSCode (or any other code editor)
• (Git version control)

Installation

1. Clone the repository (or download the zip from github):

git clone https://github.com/FrozenBirdXD/digitRecognition.git 

2. Change the file location of weights-biases.txt in the SimpleNetwork class to the relative file location e.g.: digitRecognition\\app\\src\\weights-biases.txt
3. Navigate to the project directory with the pom.xml file:

e.g.: cd digitRecognition/app

4. Build the project and install the package files:

mvn install

5. Run the 'main' method of the class called App to start the program/GUI.

Usage

To use the program run the 'main' method to start. Then just draw a digit!

Future Plans

• fix accuracy problem with GUI
• implement a convolutional neural network (CNN)
• recognize whole number not just digits
• add help section with relevant equations for machine learning as lookup

Great literature and references

The following list contains links to great articles and other helpful content I used for this project:

• Neural networks and deep learning by Michael Nielsen
• The MNIST Database by Yann LeCun, Corinna Cortes, Christopher J.C. Burges
• Deep learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville
• Performance of Matrix multiplication in Python, Java and C++ by Martin Thoma

This project is still work in progress but a "pre-release" will be created in the near future.