A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Several algorithms have been proposed to solve the problem of camera motion estimation in digital videos. However, the distinction between translation along the xaxis (y-axis) and...
Ralph Ewerth, Martin Schwalb, Paul Tessmann, Bernd...
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
In this paper, a new algorithm for robust adaptive beamforming is developed. The basic idea of the proposed algorithm is to estimate the difference between the actual and presumed...
Aboulnasr Hassanien, Sergiy A. Vorobyov, Kon Max W...