The characteristics of mobile environments, with the possibility of frequent disconnections and fluctuating bandwidth, have forced a rethink of traditional middleware. In particu...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
—Data loss in wireless sensing applications is inevitable and while there have been many attempts at coping with this issue, recent developments in the area of Compressive Sensin...
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...
Illumination conditions cause problems for many computer vision algorithms. Inparticular, shadows in an image can cause segmentation, tracking, or recognition algorithms to fail. I...
Graham D. Finlayson, Steven D. Hordley, Mark S. Dr...