We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
— In this paper we propose an exact algorithm that maximizes the sharing of partial terms in Multiple Constant Multiplication (MCM) operations. We model this problem as a Boolean...
Formal concept analysis (FCA) is increasingly applied to data mining problems, essentially as a formal framework for mining reduced representations (bases) of target pattern famili...
In this paper, we propose a tone mapping operator based on a multiscale representation pattern and on thresholds of detection contrast computed for local adaptation luminances. Th...