We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
Abstract. Although widely used to reduce error rates of difficult pattern recognition problems, multiple classifier systems are not in widespread use in off-line signature verifica...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...