diff --git a/body.tex b/body.tex
index 41061cd..739375a 100644
--- a/body.tex
+++ b/body.tex
@@ -682,7 +682,7 @@ with many detections.
             SSD with Entropy test - 0.01 conf & 0.255 & 3168 & 0.214 & 0.318 \\
             % entropy thresh: 2.4 for vanilla SSD is best
             \hline
-            Bay. SSD - no DO - 0.2 conf - no NMS \; 10 & 0.006 & 164 & 0.004 & 0.005 \\
+            Bay. SSD - no DO - 0.2 conf - no NMS \; 10 & 0.209 & 2709 & 0.300 & 0.161 \\
             no dropout - 0.2 conf - NMS \; 10 & 0.371 & \textbf{2335} & 0.365 & \textbf{0.378} \\
             0.9 keep ratio - 0.2 conf - NMS \; 10 & 0.360 & 2595 & 0.367 & 0.353 \\
             0.5 keep ratio - 0.2 conf - NMS \; 10 & 0.325 & 2759 & 0.342 & 0.311 \\
@@ -692,7 +692,7 @@ with many detections.
     \end{tabular}
     \caption{Rounded results for micro averaging. SSD with Entropy test and Bayesian SSD are represented with
     their best performing entropy threshold. Vanilla SSD with Entropy test performed best with an
-    entropy threshold of 2.4, Bayesian SSD without non-maximum suppression performed best for 0.5,
+    entropy threshold of 2.4, Bayesian SSD without non-maximum suppression performed best for 1.0,
     and Bayesian SSD with non-maximum suppression performed best for 1.4 as entropy
     threshold.
     Bayesian SSD with dropout enabled and 0.9 keep ratio performed
@@ -773,8 +773,8 @@ reported figures, such as the ones in Miller et al.~\cite{Miller2018}
             SSD with Entropy test - 0.01 conf & 0.370 & 1373 & 0.329 & \textbf{0.425} \\
             % entropy thresh: 1.7 for vanilla SSD is best
             \hline
-            Bay. SSD - no DO - 0.2 conf - no NMS \; 10 & 0.006 & 1453 & 0.009 & 0.005 \\
-            no dropout - 0.2 conf - NMS \; 10 & 0.363 & \textbf{1057} & 0.321 & 0.420 \\
+            Bay. SSD - no DO - 0.2 conf - no NMS \; 10 & 0.226 & \textbf{809} & 0.229 & 0.224 \\
+            no dropout - 0.2 conf - NMS \; 10 & 0.363 & 1057 & 0.321 & 0.420 \\
             0.9 keep ratio - 0.2 conf - NMS \; 10 & 0.354 & 1150 & 0.321 & 0.396 \\
             0.5 keep ratio - 0.2 conf - NMS \; 10 & 0.322 & 1264 & 0.307 & 0.340 \\
             % entropy thresh: 1.2 for Bayesian - 2 is best, 0.4 for 3
@@ -784,7 +784,7 @@ reported figures, such as the ones in Miller et al.~\cite{Miller2018}
     \end{tabular}
     \caption{Rounded results for macro averaging. SSD with Entropy test and Bayesian SSD are represented with
     their best performing entropy threshold. Vanilla SSD with Entropy test performed best with an
-    entropy threshold of 1.7, Bayesian SSD without non-maximum suppression performed best for 0.7,
+    entropy threshold of 1.7, Bayesian SSD without non-maximum suppression performed best for 1.5,
     and Bayesian SSD with non-maximum suppression performed best for 1.5 as entropy
     threshold. Bayesian SSD with dropout enabled and 0.9 keep ratio performed
     best for 1.7 as entropy threshold, the run with 0.5 keep ratio performed