Abstract— Design variability due to within-die and die-todie process variations has the potential to significantly reduce the maximum operating frequency and the effective yield...
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
—Our sensor selection algorithm targets the problem of global self-localization of multi-sensor mobile robots. The algorithm builds on the probabilistic reasoning using Bayes fil...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
Hidden Markov models have become the preferred technique for visual recognition of human gestures. However, the recognition rate depends on the set of visual features used, and al...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...