Clarified tables and improved their formatting

Signed-off-by: Jim Martens <github@2martens.de>
This commit is contained in:
Jim Martens 2019-09-27 15:06:58 +02:00
parent 95df9c3d31
commit e7ebea9ae8
1 changed files with 14 additions and 7 deletions

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@ -869,9 +869,16 @@ detections. Therefore, it is interesting to see the performance
of the tested variants with respect to these classes: persons, cars,
chairs, and bottles. Additionally, the results of the giraffe class are
presented as these are exceptionally good, although the class makes up
only 0.7\% of the ground truth.
only 0.7\% of the ground truth. With this share, it is below
the average of roughly 0.89\% for each of the 56 classes that make up the
second half of the ground truth.
\begin{table}[htbp]
In some cases, multiple variants have seemingly the same performance
but only one or some of them are marked bold. This is informed by
differences prior to rounding. If two or more variants are marked bold
they had the exact same performance before rounding.
\begin{table}[tbp]
\begin{tabular}{rccc}
\hline
Forward & max & Recall & Precision\\
@ -897,7 +904,7 @@ only 0.7\% of the ground truth.
\end{table}
It is clearly visible that the overall trend continues in the individual
classes (see tables \ref{tab:results-persons} through \ref{tab:results-giraffes}). However, the two vanilla SSD variants with only 0.01 confidence
classes (see tables \ref{tab:results-persons}, \ref{tab:results-cars}, \ref{tab:results-chairs}, \ref{tab:results-bottles}, and \ref{tab:results-giraffes}). However, the two vanilla SSD variants with only 0.01 confidence
threshold perform better than in the averaged results presented earlier.
Only in the chairs class, a Bayesian SSD variant performs better (in
precision) than any of the vanilla SSD variants. Moreover, there are
@ -908,7 +915,7 @@ precision than average but lower recall values for all but the Bayesian
SSD variant without NMS and dropout. Chairs and bottles perform
worse than average.
\begin{table}[htbp]
\begin{table}[tbp]
\begin{tabular}{rccc}
\hline
Forward & max & Recall & Precision\\
@ -933,7 +940,7 @@ worse than average.
\label{tab:results-cars}
\end{table}
\begin{table}[htbp]
\begin{table}[tbp]
\begin{tabular}{rccc}
\hline
Forward & max & Recall & Precision\\
@ -959,7 +966,7 @@ worse than average.
\end{table}
\begin{table}[htbp]
\begin{table}[tbp]
\begin{tabular}{rccc}
\hline
Forward & max & Recall & Precision\\
@ -984,7 +991,7 @@ worse than average.
\label{tab:results-bottles}
\end{table}
\begin{table}[htbp]
\begin{table}[tbp]
\begin{tabular}{rccc}
\hline
Forward & max & Recall & Precision\\