diff --git a/body_expose.tex b/body_expose.tex
index 428ec79..ca94992 100644
--- a/body_expose.tex
+++ b/body_expose.tex
@@ -2,7 +2,7 @@
 
 \chapter{Introduction}
 
-\section{Motivation}
+\subsection*{Motivation}
 
 Famous examples like the automatic soap dispenser which does not
 recognize the hand of a black person but dispenses soap when presented
@@ -50,7 +50,7 @@ describes tasks where the network is supposed to identify the
 class of any given input. In this thesis, I will focus on
 classification.
 
-\section{Object detection in open-set conditions}
+\subsection*{Object detection in open-set conditions}
 
 More specifically, I will look at object detection in the open-set
 conditions. In non-technical words this effectively describes
@@ -108,7 +108,7 @@ auto-encoder, a novelty score is calculated. A low novelty
 score signals a known object. The opposite is true for a high
 novelty score.
 
-\section{Research question}
+\subsection*{Research question}
 
 Given these two approaches to solve the explanation task of above,
 it comes down to performance. At the end of the day the best