We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
As the accuracy of conventional classifiers, based only on a static partitioning of feature space, appears to be approaching a limit, it may be useful to consider alternative appro...
Computer problem diagnosis remains a serious challenge to users and support professionals. Traditional troubleshooting methods relying heavily on human intervention make the proce...
Chun Yuan, Ni Lao, Ji-Rong Wen, Jiwei Li, Zheng Zh...