In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
The increasing use of multimedia streams nowadays necessitates the development of efficient and effective methodologies for manipulating databases storing them. Moreover, content-...
In this study, we propose two algorithms for measuring the distance between shape boundaries. In the algorithms, shape boundary is represented by the Beam Angle Statistics (BAS), w...
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
We introduce a new domain-independent framework for formulating and efficiently evaluating similarity queries over historical data, where given a history as a sequence of timestam...