: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Abstract. Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation. However, the availability of comprehensive, reliable and suitable manual segmen...
Tammy Riklin-Raviv, Koen Van Leemput, Bjoern H. Me...
Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independen...
In this paper, we aim to reconstruct free-form 3D models from only one or few silhouettes by learning the prior knowledge of a specific class of objects. Instead of heuristically...
This paper addresses the problem of tracking objects which undergo rapid and significant appearance changes. We propose a novel coupled-layer visual model that combines the targe...