Abstract. Several sources of uncertainties in shape boundaries in medical images have motivated the use of probabilistic labeling approaches. Although it is well-known that the sam...
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Abstract. Task-structured probabilistic input/output automata (taskPIOAs) are concurrent probabilistic automata that, among other things, have been used to provide a formal framewo...
Aaron D. Jaggard, Catherine Meadows, Michael Mislo...
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
In this paper we introduce a new deformable model, called eigensnake, for segmentation of elongated structures in a probabilistic framework. Instead of snake attraction by speciï¬...