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...
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we conside...
Keeping track of changes in user interests from a document stream with a few relevance judgments is not an easy task. To tackle this problem, we propose a novel method that integr...
We propose a new technique for the efficient search and navigation in XML documents and streams. This technique takes string matching algorithms designed for efficient keyword sear...
Christoph Koch, Stefanie Scherzinger, Michael Schm...
This paper presents the application of cognitive algorithm for a stream diffusion in home theatre “5+1 audio” surround applications. We develop a wavelet-based method to effic...