In many classification and data-mining applications the user does not know a priori which distance measure is the most appropriate for the task at hand without examining the produ...
Based on a series of known and new examples, we propose the generalized setting of “distance from triviality” measurement as a reasonable and prospective way of determining use...
This paper introduces a supervised discriminant Hausdorff distance that fits into the framework for automatic face analysis and recognition proposed in [1]. Our proposal relies so...
We describe a method for learning statistical models of images using a second-order hidden Markov mesh model. First, an image can be segmented in a way that best matches its stati...
Daniel DeMenthon, David S. Doermann, Marc Vuilleum...
Abstract. We propose inductive distance-based methods for instance classification and retrieval in ontologies. Casting retrieval as a classification problem with the goal of assess...