Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
This paper focuses on matching 1D structures by variational methods. We provide rigorous rules for the construction of the cost function, on the basis of an analysis of properties ...
In previous work on point matching, a set of points is often treated as an instance of a joint distribution to exploit global relationships in the point set. For nonrigid shapes, h...
To enhance UDDI query capability, typically based on taxonomic classification, semantic matching is assuming a key role. Even if we recognize the great importance of semantics in ...
Abstract The most common matching applications, e.g., ontology matching, focus on the computation of the correspondences holding between the nodes of graph structures (e.g., concep...