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diff --git a/report2/metadata.yaml b/report2/metadata.yaml deleted file mode 100755 index 5f9f737..0000000 --- a/report2/metadata.yaml +++ /dev/null @@ -1,21 +0,0 @@ ---- -title: 'EE4-68 Pattern Recognition (2018-2019) CW2' -author: - - name: Vasil Zlatanov (01120518), Nunzio Pucci (01113180) - email: vz215@ic.ac.uk, np1915@ic.ac.uk - link: 'Sources: < [git](https://git.skozl.com/e4-pattern/) - [tar](https://git.skozl.com/e4-pattern/snapshot/vz215_np1915-master.tar.gz) - [zip](https://git.skozl.com/e4-pattern/snapshot/vz215_np1915-master.zip) >' -numbersections: yes -lang: en -babel-lang: english -nocite: | - @deepreid, @sklearn - -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 evaluated 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 $N$. -... - |