Titlebook: Maximum Entropy and Bayesian Methods; Boise, Idaho, USA, 1 Gary J. Erickson,Joshua T. Rychert,C. Ray Smith Conference proceedings 1998 Spri

Herd-Immunity

JIBE

胰臟

催眠藥

平庸的人或物

overhaul

Neuralgia

FICE

Integrated Deformable Boundary Finding Using Bayesian Strategies,tion is achieved in this work by using region information in addition to gradient information within the deformable boundary finding framework. The integration problem is framed in a Bayesian framework using shape and region priors to influence a gradient-based deformable boundary finding.

Bumble

Shape Reconstruction in X-Ray Tomography from a Small Number of Projections Using Deformable Modelsolygonal shapes with very small number of vertices, snakes and deformable templates) and these parameters are estimated either by least squares or by maximum likelihood methods. We propose modeling the shape of the fault region by a polygon with a large number of vertices, allowing modeling of nearl

Overstate

Difficulties Applying Recent Blind Source Separation Techniques to EEG and MEG,ineffective when applied to EEG or MEG signals. Many of these techniques implicitly assume that the source distributions have a large kurtosis, whereas an analysis of EEG/MEG signals reveals that the distributions are multimodal. This suggests that more effective separation techniques could be desig