1 files changed, 5 insertions, 6 deletions
diff --git a/report/paper.md b/report/paper.md
index da00b3f..7c91d0f 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -114,9 +114,8 @@ The analysed classification methods used for face recognition are Nearest Neighb
 alternative method utilising reconstruction error. 
 
 Nearest Neighbor projects the test data onto the generated subspace and finds the closest 
-training sample to the projected test image, assigning the same class as that of the nearest neighbor.
-
-Recognition accuracy of NN classification can be observed in figure \ref{fig:accuracy}.
+training sample to the projected test image, assigning the same class as that of the nearest neighbor. Recognition accuracy 
+of NN classification can be observed in figure \ref{fig:accuracy}.
 
 A confusion matrix showing success and failure cases for Nearest Neighbor classification when using PCA can be observed in figure \ref{fig:cm}:
 
@@ -184,7 +183,7 @@ memory associated with storing the different eigenvectors is deallocated, the to
 \end{center}
 \end{figure}
 
-A confusion matrix showing success and failure cases for alternative method classification
+A confusion matrix showing success and failure cases for alternative method
 can be observed in figure \ref{fig:cm-alt}.
 
 \begin{figure}
@@ -531,8 +530,8 @@ LDA-PCA & 0.11		& 0.19		& 0.13		\\ \hline
 
 \begin{figure}
 \begin{center}
-\includegraphics[width=15em]{fig/memnn.pdf}
-\includegraphics[width=15em]{fig/memalt.pdf}
+\includegraphics{fig/memnn.pdf}
+\includegraphics{fig/memalt.pdf}
 \caption{Memory Usage for NN and alternative method}
 \label{fig:mem}
 \end{center}