The classical case of morphological segmentation is based on the watershed transform, constructed by flooding the gradient image, which is seen as a topographic surface, with cons...
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Software development in general and groupware applications in particular can greatly benefit from the reusability and interoperability aspects associated with software components....
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...