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authornunzip <np.scarh@gmail.com>2018-12-14 12:35:37 +0000
committernunzip <np.scarh@gmail.com>2018-12-14 12:35:37 +0000
commit8dad008167c2a7d9402947f6e5234ca752b7b099 (patch)
tree9bb8406d452292b4dfb31abcef54214ca0831d84 /report/metadata.yaml
parent1a67e68bd1b51b7a0ef860542a5ab488384d91b4 (diff)
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Change 'neighbors' to 'neighbours'HEADmaster
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@@ -13,7 +13,7 @@ nocite: |
abstract: |
This report analyses distance metrics learning techniques with regards to
identification accuracy for the dataset CUHK03. The baseline method used for
- identification is Nearest Neighbors based on Euclidean distance.
+ identification is Nearest Neighbours based on Euclidean distance.
The improved approach evaluated utilises Jaccardian metrics to rearrange the NN
ranklist based on reciprocal neighbours. While this approach is more complex and introduces new hyperparameters,
significant accuracy improvements are observed -