Download Digit Recognition Using Machine Learning

Digit Recognition Using
Machine Learning
Matheus Lelis
University of Massachusetts: Dartmouth
Abstract

The goal of this research project is to use an artificial
neural network machine learning algorithms with back
propagation to develop a program which will recognize
handwritten letters and numbers.
Background
Artificial Neural Network

An artificial neural network
learning algorithm is a learning
algorithm that is inspired by the
structure and functional aspects of
biological neural networks.

Computations are structured in
terms of an interconnected group
of artificial neurons, processing
information using a connectionist
approach to computation.
Problem
Character Recognition

Reading in the images of
handwritten numbers and
letters and outputting the
machine-encoded version.

Adding distortion to try to
solve CAPTCHAs.
Progress
The machine was written
using MATLAB works in
two steps.
1st step – runs through a set
of data and learns and sets
weight
2nd step – runs through new
data and tries to guess.
It takes in a matrix of data
with images 20px by 20px
Issues

Finding/Creating new data to test the machine with.

Teaching the machine to work with letters, only works
with numbers for now.

Adding the distortion and test out the CAPTCHAs.