On the basis of a case-study, we demonstrate the usefulness of topology invariants for model-driven systems development. Considering a graph grammar semantics for a relevant fragme...
We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...
Images of an object undergoing ego- or camera- motion
often appear to be scaled, rotated, and deformed versions
of each other. To detect and match such distorted patterns
to a s...
A general framework for typing graph rewriting systems is presented: the idea is to statically derive a type graph from a given graph. In contrast to the original graph, the type g...
Graph structures have been proved important in high level-vision since they can be used to represent structural and relational arrangements of objects in a scene. One of the probl...