The study of communities in social networks has attracted considerable interest from many disciplines. Most studies have focused on static networks, and in doing so, have neglected...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Abstract— Most large-scale public environments provide direction signs to facilitate the orientation for humans and to find their way to a goal location in the environment. Thus...
We are interested in the challenging scientific pursuit of how to characterize human activities in any formal meeting situation by tracking people’s positions with a computer vi...
Building applications over Linked Data often requires a mapping between the application model and the ontology underlying the source dataset in the Linked Data cloud. This mapping ...