We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
We tackle the problem of object recognition using a Bayesian approach. A marked point process [1] is used as a prior model for the (unknown number of) objects. A sample is generat...
This paper presents a general approach to modeling VBR (variable bit rate) compressed full-motion video. The salient feature of such video is the existence of scenes. Scene struct...