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We present a new approach to compute the graph edit distance between two attributed graphs which is based on a formal connection between the graph edit distance problem and that of finding a dominant set in an auxiliary edge-weighted “association” graph. Experiments performed on various data sets show that with the proposed approach we are able to improve on state-of-the-art algorithms.
This paper explores the classification problem based on parallel feature partitioning. This formulation leads to a new problem in computational geometry. While this new problem appears to be NP-complete, it is shown that the proposed graph theoretical platform makes it semi-tractable, allowing the use of conventional tools for its solution. Here, by conventional, we mean any exact or heuristic algorithm...
A computational saliency model utilizing bio-inspired features for spatiotemporal saliency is presented in this paper. We first propose distributed opponent oriented energy for compact local dynamic texture description motivated by Human Vision System. Then, we integrate the derived motion characterization and a revised self-resemblance saliency framework. High effectiveness and efficiency of the...
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