Minor report additions

mini_proj/report/references.bib

@@ -137,3 +137,12 @@ month={Nov},}
  pages={2825--2830},
  year={2011}
 }
+@misc{bilogur_2017, 
+title={Where's Waldo | Kaggle}, 
+url={https://www.kaggle.com/residentmario/wheres-waldo}, 
+journal={Countries of the World | Kaggle}, 
+publisher={Aleksey Bilogur}, 
+author={Bilogur, Aleksey}, 
+year={2017}, 
+month={Oct}
+}

mini_proj/report/waldo.tex

@@ -279,11 +279,11 @@
 				\hline
 				\textbf{Method} & \textbf{Test Accuracy} & \textbf{Training Time (s)}\\
 				\hline
-				LeNet & 87.86\% & 65.67\\
+				LeNet & 89.81\% & 58.13\\
 				\hline
-				CNN & \textbf{95.63\%} & 119.31\\
+				CNN & \textbf{95.63\%} & 113.81\\
 				\hline
-				FCN & 94.66\% & 113.94\\
+				FCN & 94.66\% & 117.69\\
 				\hline
 				Support Vector Machine & 83.50\% & 5.90\\
 				\hline
@@ -300,7 +300,7 @@
 			\label{tab:results}
 		\end{table}
     
-    We can see by the results that Deep Neural Networks outperform our benchmark
+    We can see by in these results that Deep Neural Networks outperform our benchmark
     classification models, although the time required to train these networks is
     significantly greater.
     
@@ -322,7 +322,14 @@
 	There might be quite a lot of ground that could be gained by using
 	specialized variants of these clustering algorithms.
 
-		\clearpage          % Ensures that the references are on a seperate page
+
+	Discussion of the results:
+	- Was this what we expected to see?
+	- What was surprising?
+	- If you take learning time into account, are NN still as good?
+	- We also did say we would have these other measures, so we should at least try to include them. Then the question is also what do they show.
+
+		\clearpage          % Ensures that the references are on a separate page
 		\pagebreak
 		\bibliographystyle{alpha}
 		\bibliography{references}