Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
We developed a new approach for the reconstruction of phylogenetic trees using ant colony optimization metaheuristics.Atree is constructed using a fully connected graph and the pro...
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Various research papers question and analyze the maturity of the e-government research area and its stance as a scientific discipline. The common conclusion of these papers is the...