We study the problem of visualizing large networks and develop es for effectively abstracting a network and reducing the size to a level that can be clearly viewed. Our size reduc...
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Abstract. Transmission Ultrasound Computed Tomography (CT) is strongly affected by the acoustic refraction properties of the imaged tissue, and proper modeling and correction of th...
Shengying Li, Klaus Mueller, Marcel Jackowski, ...
Abstract. This paper presents a novel approach for image segmentation by introducing competition between neighboring shape models. Our method is motivated by the observation that e...
Pingkun Yan, Weijia Shen, Ashraf A. Kassim, Mubara...
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...