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authornunzip <np.scarh@gmail.com>2018-12-10 16:33:11 +0000
committernunzip <np.scarh@gmail.com>2018-12-10 16:33:11 +0000
commit62a695d43a2b64295ec718826cc7a33e39e983e2 (patch)
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parent8874aec6c05402f05b2b01b8b907dd8f8468719d (diff)
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Merge branch 'master' of git.skozl.com:e4-pattern
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-rwxr-xr-xreport2/metadata.yaml7
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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 $N$.
...