A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...
Image based rendering is an attractive alternative for generating novel views compared to model based rendering due to its lower complexity and potential for photo-realistic resul...
Image-analysis methods play an important role in helping detect brain changes in and diagnosis of Alzheimer's Disease (AD). In this paper, we propose an automatic unsupervised...
The topic of this paper is the integration of Expectation Maximization (EM) background modeling and template matching using color histograms as templates to improve person trackin...
Paul J. Withagen, Klamer Schutte, Frans C. A. Groe...
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...