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Added another section to allow covering the GPND in detail 

Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens 2019-03-07 15:07:12 +01:00
parent 9a1bd269fd
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body_expose.tex
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@ -235,15 +235,15 @@ detections for unknown object classes have a higher label
uncertainty. A treshold on the entropy \(H(\mathbf{q}_i)\) can then
be used to identify and reject these false positive cases.
\section{GPND}
\section{Generative Probabilistic Novelty Detection}
For the theoretical underpinning of the Generative Probabilistic
Novelty Detection the reader is advised to refer to the paper of
Pidhorskyi et al\cite{Pidhorskyi2018}. This section will only
cover the key aspects of an adversarial auto-encoder required
to understand their method.
% TODO Write about GPND in understandable terms
\subsection{Adversarial Auto-encoder}
\section{Adversarial Auto-encoder}
This section will explain the adversarial auto-encoder used by
Pidhorskyi et al\cite{Pidhorskyi2018} but in a slightly modified
form to make it more understandable.
The training data points \(x_i \in \mathbb{R}^m \) are the input
of the auto-encoder. An encoding function \(e: \mathbb{R}^m \rightarrow \mathbb{R}^n\) takes the data points