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author | nunzip <np.scarh@gmail.com> | 2018-12-14 12:08:50 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2018-12-14 12:08:50 +0000 |
commit | ed2536b2fbb570302e77468e4b2014f7cdc4c771 (patch) | |
tree | 4328315d923af7d2848895a9ff8ddb4df74a7b01 /report | |
parent | bc4aceea287176c4f6050ccd1c67339e774ea6aa (diff) | |
download | vz215_np1915-ed2536b2fbb570302e77468e4b2014f7cdc4c771.tar.gz vz215_np1915-ed2536b2fbb570302e77468e4b2014f7cdc4c771.tar.bz2 vz215_np1915-ed2536b2fbb570302e77468e4b2014f7cdc4c771.zip |
Adapt to 4 pages
Diffstat (limited to 'report')
-rw-r--r-- | report/paper.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/report/paper.md b/report/paper.md index 6ebf32d..2a9add2 100644 --- a/report/paper.md +++ b/report/paper.md @@ -66,7 +66,7 @@ identification is shown in red. \begin{figure} \begin{center} -\includegraphics[width=22em]{fig/eucranklist.png} +\includegraphics[width=24em]{fig/eucranklist.png} \caption{Top 10 rank-list generated for 5 query images} \label{fig:eucrank} \end{center} @@ -108,7 +108,7 @@ improve identification accuracy, we consider it an additional baseline. \begin{figure} \begin{center} -\includegraphics[width=17em]{fig/kmeanacc.pdf} +\includegraphics[width=20em]{fig/kmeanacc.pdf} \caption{Top 1 Identification accuracy varying $k$-Means cluster size} \label{fig:kmeans} \end{center} @@ -249,7 +249,7 @@ The difference between the top $k$ accuracies of the two methods gets smaller as \begin{figure} \begin{center} -\includegraphics[width=20em]{fig/comparison.pdf} +\includegraphics[width=24em]{fig/comparison.pdf} \caption{Top K (@rank) Identification accuracy ($K_L=0.3$,$k_1=9$,$k_2=3$)} \label{fig:compare} \end{center} |