We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...
The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectra...
Yuliya Tarabalka, James C. Tilton, Jon Atli Benedi...
Abstract. In this paper we describe the application of a novel statistical videomodeling scheme to sequences of multiple sclerosis (MS) images taken over time. The analysis of the ...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...