In this paper we present a new density estimation algorithm using mixtures of mixtures of Gaussians. The new algorithm overcomes the limitations of the popular Expectation Maximiza...
This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
A common problem in most active contour methods is that the recursive searching scheme can only return a local optimal solution. Furthermore, the internal energy of the snake is n...
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...