This paper presents a learning system that uses genetic programming as a tool for automatically inferring the set of classification rules to be used during a preclassification sta...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
—This paper describes a unified data model that represents multimedia, timeline, and simulation data utilizing a single set of related data modeling constructs. A uniform model f...
—This paper presents a new framework for the completion of missing information based on local structures. It poses the task of completion as a global optimization problem with a ...
In this paper, we present a novel methodology to detect and recognize objects in cluttered scenes by proposing boosted contextual descriptors of landmarks in a framework of multi-...
We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as ...