Abstract. We propose a semi-supervised, kinetic modeling based segmentation technique for molecular imaging applications. It is an iterative, self-learning algorithm based on uncer...
Ahmed Saad, Benjamin Smith 0002, Ghassan Hamarneh,...
We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to p...
Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grz...
Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...
In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians...
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...