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authorVasil Zlatanov <v@skozl.com>2018-12-10 16:17:22 +0000
committerVasil Zlatanov <v@skozl.com>2018-12-10 16:17:22 +0000
commit61a972f93c94f276aeffd4fded902810117d2391 (patch)
treea8dbdb2dd778e46b135a915b0563394c2f321726 /report2
parentcc0ce36fb75f4b207311c07daf86b835aea0a745 (diff)
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Add nice abstract
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-rwxr-xr-xreport2/metadata.yaml7
1 files changed, 6 insertions, 1 deletions
diff --git a/report2/metadata.yaml b/report2/metadata.yaml
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@@ -7,6 +7,11 @@ numbersections: yes
lang: en
babel-lang: english
abstract: |
-
+ This report analyses distance metrics learning techniques with regards to
+ identification accuracy for the dataset CUHK03. The baseline method used for
+ identification is Eucdidian based Nearest Neighbors based on Euclidean distance.
+ The improved approach we propose utilises Jaccardian metrics to rearrange the NN
+ ranklist based on reciprocal neighbours. While this approach is more complex and introduced new hyperparameter, significant accuracy improvements are observed -
+ approximately 10% increased Top-1 identifications, and good improvements for Top-$N$ accuracy with low $N$.
...