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Jip J. Dekker 2018-05-25 12:13:57 +10:00
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\begin{document} \begin{document}
\title{What is Waldo?} \title{What is Waldo?}
\author{Kelvin Davis \and Jip J. Dekker\and Anthony Silvestere} \author{Kelvin Davis \and Jip J. Dekker \and Anthony Silvestere}
\maketitle \maketitle
\begin{abstract} \begin{abstract}
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The famous brand of picture puzzles ``Where's Waldo?'' relates well to many
unsolved image classification problem. This offers us the opportunity to
test different image classification methods on a data set that is both small
enough to compute in a reasonable time span and easy for humans to
understand. In this report we compare the well known machine learning
methods Naive Bayes, Support Vector Machines, $k$-Nearest Neighbors, and
Random Forest against the Neural Network Architectures LeNet, Fully
Convolutional Neural Networks, and Fully Convolutional Neural Networks.
\todo{I don't like this big summation but I think it is the important
information}
Our comparison shows that \todo{...}
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\end{abstract} \end{abstract}
\section{Introduction} \section{Introduction}