Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Abstract. We introduce a value-based noise reduction method for DualEnergy CT applications. It is based on joint intensity statistics estimated from high- and low-energy CT scans o...
Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their...
As an alternative to vector representations, a recent trend in image classification suggests to integrate additional structural information in the description of images in order to...