remove passive-aggressive rant

tex/explanation.tex

@@ -263,7 +263,7 @@ \subsubsection{Data Handling}
 \end{figure}
 The deepVO model is trained by pairwise stacked images in a sequence. Each batch contains a preset number of these sequences. The \texttt{DataManager} is used to arrange the data in this format. Each image has to be stacked with its previous image. This operation is performed by an index shift over the list of images as depicted in \autoref{fig:image_stacking}. Each batch includes different non overlapping sequences of image stacks and
 poses. Each image stack is labeled by a seperate pose, which is relative to the
-first pose of the sequence. 
+first pose of the sequence.
 This is calculated by the difference of the current pose in the sequence and the first pose to get the relative distance of these two poses. The angle distance of angle a and b is defined as:
 
 \begin{equation}
@@ -274,7 +274,7 @@ \subsubsection{Data Handling}
 parameter \texttt{train\_test\_ratio} determines the ratio of training to testing
 batches and defaults to 70\% training batches and 30\% test batches. After an
 epoch the training batches and test batches are be shuffled in order to avoid learning
-sequential relationships. Because of the high memory consumption of the deepVO model, 
+sequential relationships. Because of the high memory consumption of the deepVO model,
 the DataManager has to spare the memory by loading only the currently required batches.
 
 
@@ -316,11 +316,11 @@ \subsection{Results}
 % ---------------------- %
 % SUBSECTION: GREETINGS %
 % ---------------------- %
-\section{Room for Nonsense}
-\label{sec:nonsense}
-The authors would like to thank Thomes Wiemann for repeatedly failing to follow
-through on his promise to secure an Nvidia hardware grant in order to obtain a
-potent graphics card.
+% \section{Room for Nonsense}
+% \label{sec:nonsense}
+% The authors would like to thank Thomes Wiemann for repeatedly failing to follow
+% through on his promise to secure an Nvidia hardware grant in order to obtain a
+% potent graphics card.
 
 
 % --------------------- %