?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Scientific workflow tools allow users to specify complex computational experiments and provide a good framework for robust science and engineering. Workflows consist of pipelines ...
David Abramson, Blair Bethwaite, Colin Enticott, S...
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
We propose a system architecture for real-time hardware speech recognition on low-cost, power-constrained devices. The system is intended to support real-time speech-based user in...