In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
In this multi-university collaborative research, we will develop a framework for the dynamic data-driven fault diagnosis of wind turbines which aims at making the wind energy a com...
Yu Ding, Eunshin Byon, Chiwoo Park, Jiong Tang, Yi...
We consider random graphs, and their extensions to random structures, with edge probabilities of the form βn−α , where n is the number of vertices, α, β are fixed and α >...
We discuss the properties of force-feedback haptic simulation systems that fundamentally limit the re-creation of periodic gratings, and hence, of any texture. These include sampl...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...