Purpose:
To design a system to reliably perform image recognition using neural networks, and to develop a proof of concept program to demonstrate this.
Background:
Neural networks have been used extensively to classify data and recognize patterns and trends in various types of data. For example, in the financial sector neural networks have been used to predict stock prices based on past trends. Neural networks perform especially well for finding patterns in highly complex data sets. In my project I wanted to use neural networks to do image recognition, and object recognition within images. There have been previous attempts to do this before, but they ultimately failed due to the fact there was no way to universally represent an image to a neural network. Developments have recently been made that allow one to represent the key points of an image mathematically. In my project I hope to bring the adaptive nature of neural networks together with the ability to represent an image as a series of universal vectors to do reliable and robust image recognition.