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Improved start of methods chapter 

Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens 2019-08-13 13:15:48 +02:00
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@ -366,26 +366,17 @@ be used to identify and reject these false positive cases.
\label{chap:methods}
This chapter starts with the design of the source code; the
source code is so much more than a means to an end. The thesis
uses two data sets: MS COCO and SceneNet RGB-D; a section
will explain how these data sets have been prepared.
Afterwards the replication of the work of Miller et al. is
outlined, followed by the implementation of the auto-encoder.
This chapter explains the functionality of the Bayesian SSD and
provides some information on the software and source code design.
In particular, the model architecture of both vanilla SSD and
Bayesian SSD, the calculation of model uncertainty, and relevant
implementation details will be presented.
\section{Bayesian SSD for Novelty Detection}
\section{Bayesian SSD for Model Uncertainty}
\subsection{Model Architecture}
\subsection{Novelty Detection}
\subsection{Implementation Details}
\section{Auto-encoder for Novelty Detection}
\subsection{Model Architecture}
\subsection{Novelty Detection}
\subsection{Model Uncertainty}
\subsection{Implementation Details}