The movement to multi-core processors increases the need for simpler, more robust parallel programming models. Atomic sections have been widely recognized for their ease of use. T...
Bill McCloskey, Feng Zhou, David Gay, Eric A. Brew...
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Analysis of videos of human-object interactions involves understanding human movements, locating and recognizing objects and observing the effects of human movements on those obje...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle pe...