Current methods for selectivity estimation fall into two broad categories, synopsis-based and sampling-based. Synopsis-based methods, such as histograms, incur minimal overhead at ...
Abstract. This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric m...
Abstract. Image segmentation techniques typically require proper weighting of competing data fidelity and regularization terms. Conventionally, the associated parameters are set t...
In this paper, we propose a novel technique for estimating focused image sequences captured by an out-of-focus camera. The basic concept used in the proposed algorithm employs mul...
This paper presents a novel way of improving POS tagging on heterogeneous data. First, two separate models are trained (generalized and domain-specific) from the same data set by...