160 search results - page 16 / 32 » Maximum a posteriori based regularization parameter selectio... |
BMEI
2009
IEEE
13 years 9 months ago
2009
IEEE
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
PAMI
2010
13 years 3 months ago
2010
We present a new method for blind document bleed through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate pri...
FUZZY
2001
Springer
14 years 1 months ago
2001
Springer
Simulated annealing is a general optimisation algorithm, based on hill-climbing. As in hill-climbing, new candidate solutions are selected from the ‘neighbourhood’ of the curre...
PRL
2007
13 years 8 months ago
2007
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
ISBI
2008
IEEE
14 years 9 months ago
2008
IEEE
We investigate the problem of automatic tuning of a deconvolution algorithm for three-dimensional (3D) fluorescence microscopy; specifically, the selection of the regularization p...