Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...
Abstract. Although widely used to reduce error rates of difficult pattern recognition problems, multiple classifier systems are not in widespread use in off-line signature verifica...
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
The purpose of this study is to construct a high-order interpolation scheme for arbitrary scattered datasets. The resulting function approximation is an interpolation function when...
In this paper, we introduce a novel iterative motion tracking
framework that combines 3D tracking techniques with
motion retrieval for stabilizing markerless human motion
captur...
Andreas Baak, Bodo Rosenhahn, Meinard Muller, Hans...