From df249ee272322795b8ef58fe481a6c1bc0698fdf Mon Sep 17 00:00:00 2001 From: Jim Martens Date: Thu, 19 Sep 2019 15:11:35 +0200 Subject: [PATCH] Shortened qualitative analysis Signed-off-by: Jim Martens --- body.tex | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/body.tex b/body.tex index d7dece4..02c8bff 100644 --- a/body.tex +++ b/body.tex @@ -861,7 +861,7 @@ reported figures, such as the ones in Miller et al.~\cite{Miller2018} % TODO: expand -This subsection focuses not on the big picture but compares vanilla SSD +This subsection compares vanilla SSD with Bayesian SSD with respect to specific images that illustrate similarities and differences between both approaches. For this comparison, 0.2 confidence threshold is applied. Furthermore, Bayesian @@ -881,28 +881,28 @@ SSD uses non-maximum suppression and dropout with 0.9 keep ratio. \end{minipage} \end{figure} -In the ground truth, only a stop sign and a truck are detected. The differences between vanilla SSD and Bayesian SSD are almost not visible -(see figures \ref{fig:stop-sign-truck-vanilla} and \ref{fig:stop-sign-truck-bayesian}). The truck is neither detected by vanilla nor Bayesian SSD. Instead both detected a pottet plant and a traffic light. The stop sign is detected by both variants. +The ground truth only contains a stop sign and a truck. The differences between vanilla SSD and Bayesian SSD are almost not visible +(see figures \ref{fig:stop-sign-truck-vanilla} and \ref{fig:stop-sign-truck-bayesian}): the truck is neither detected by vanilla nor Bayesian SSD, instead both detected a pottet plant and a traffic light. The stop sign is detected by both variants. This behaviour implies problems with detecting objects at the edge -that overwhelmingly lie outside the image frame. Furthermore, the predictions are usually identical - when rounding to three digits. +that overwhelmingly lie outside the image frame. Furthermore, the predictions are usually identical. \begin{figure} \begin{minipage}[t]{0.48\textwidth} \includegraphics[width=\textwidth]{COCO_val2014_000000403817_bboxes_vanilla} - \caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red. Predictions are from vanilla SSD.} + \caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red and rounded to three digits. Predictions are from vanilla SSD.} \label{fig:cat-laptop-vanilla} \end{minipage}% \hfill \begin{minipage}[t]{0.48\textwidth} \includegraphics[width=\textwidth]{COCO_val2014_000000403817_bboxes_bayesian} - \caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red. Predictions are from Bayesian SSD with 0.9 keep ratio.} + \caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red and rounded to three digits. Predictions are from Bayesian SSD with 0.9 keep ratio.} \label{fig:cat-laptop-bayesian} \end{minipage} \end{figure} Another example (see figures \ref{fig:cat-laptop-vanilla} and \ref{fig:cat-laptop-bayesian}) is a cat with a laptop/TV in the background on the right side. Both variants detect a cat but the vanilla variant detects a dog as well. The laptop and TV are not detected but this is expected since -the classes were not trained. +these classes were not trained. \chapter{Discussion and Outlook}