The aim of this paper is to present a dissimilarity measure strategy by which a new philosophy for pattern classification pertaining to dissimilaritybased classifications (DBCs) ca...
A similarity measure is described that does not require the prior specification of features or the need for training sets of representative data. Instead large numbers of feature...
We describe how to teach deformable models to maximize image segmentation correctness based on user-specified criteria, and we present a method for evaluating which criteria work ...
In this paper, we compared three kinds of similarity measures for DP-matching based query-by-humming music retrieval experiments. First, a DP matching-based algorithm is formulate...
We investigate the symmetric Kullback-Leibler (KL2) distance in speaker clustering and its unreported effects for differently-sized feature matrices. Speaker data is represented a...