From 2a5c62f9ea50971ba25c3e8f519e224093ec0090 Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Mon, 10 Dec 2018 17:21:38 +0000 Subject: s/propose/evaluate/ --- report2/metadata.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/report2/metadata.yaml b/report2/metadata.yaml index f35d6aa..20375f9 100755 --- a/report2/metadata.yaml +++ b/report2/metadata.yaml @@ -10,7 +10,7 @@ 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 + 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 $N$. ... -- cgit v1.2.3-54-g00ecf