Starting from a compositional operational semantics of transition P Systems we have previously defined, we face the problem of developing an axiomatization that is sound and comple...
Roberto Barbuti, Andrea Maggiolo-Schettini, Paolo ...
We propose a new variational method to restore point-like and curvelike singularities in 2-D images. As points and open curves are fine structures, they are difficult to restore...
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
We initiate a new line of investigation into online property-preserving data reconstruction. Consider a dataset which is assumed to satisfy various (known) structural properties; e...
Nir Ailon, Bernard Chazelle, Seshadhri Comandur, D...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...