This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmenta...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Social networking has provided powerful new ways to find people, organize groups, and share information. Recently, the potential functionalities of the ubiquitous infrastructure le...