This paper deals with the problem of statistical unsupervised fusion of dependent sensors with its potential applications to multisensor image segmentation. On the one hand, Bayes...
In this paper we propose an efficient unsupervised texture segmentation method. We introduce the extension of a state-of-the-art segmentation algorithm, which is exclusively based...
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
We propose a new probabilistic approach to information retrieval based upon the ideas and methods of statistical machine translation. The central ingredient in this approach is a ...
We develop a statistical framework for the simultaneous, unsupervised segmentation and discovery of visual object categories from image databases. Examining a large set of manuall...