We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...
We present the modeling of the high-level design of a next generation network switch from the perspective of a ComputerAided Design (CAD) team within the larger context of a desig...
Andrew S. Cassidy, Christopher P. Andrews, Donald ...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
An event-based solution that uses events to convey information to a monitoring tool is well suited to implementing a non-intrusive monitoring infrastructure. This enables an SOA s...
This paper describes a novel system for building seamless texture maps for a surface of arbitrary topology from real images of the object taken with a standard digital camera and ...