This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
This paper describes a framework for the estimation of shape from sparse or incomplete range data. It uses a shape representation called blending, which allows for the geometric c...
Abstract: Recently a growing demand has arisen for methods for the development of smalland medium scale Web Information Systems (WIS). Web applications are being built in a rapidly...
SNOMED CT (SCT) has been designed and implemented in an era when health computer systems generally required terminology representations in the form of singular precoordinated conc...
Peter MacIsaac, Donald Walker, Rachel L. Richesson...
In this paper, we introduce a first-order probabilistic model that combines multiple cues to classify human activities from video data accurately and robustly. Our system works in...