This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system,...
Stochastic grammar has been used in many video analysis and event recognition applications as an efficient model to represent large-scale video activity. However, in previous works...
In structural character recognition, a character is usually viewed as a set of strokes and the spatial relationships between them. In this paper, we propose a stochastic modeling ...
Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we con...