We vary the quantization parameter in H.264 video encoding by increasing it by a well-chosen offset in every other frame, which we call reduced frames. As the motion compensation ...
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
We experimentally evaluate bagging and six other randomization-based approaches to creating an ensemble of decision-tree classifiers. Bagging uses randomization to create multipl...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
Abstract. One of the potential advantages of multiple classifier systems is an increased robustness to noise and other imperfections in data. Previous experiments on classificati...
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar