In this paper we present a new framework for image segmentation using probabilistic multinets. We apply this framework to integration of regionbased and contour-based segmentation ...
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
We study the extension of applicability of system-level testing techniques to the construction of a consistent model of (legacy) systems under test, which are seen as black boxes....
This experience paper presents observations, lessons learned, and recommendations based on a case study of reuse. The case study is concerned with the development, maturation, and...
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of ...