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ICPR
2006
IEEE
16 years 7 months ago
Wavelet denoising of multicomponent images, using a Gaussian Scale Mixture model
In this paper, denoising on multicomponent images is performed. The presented procedure is a spatial waveletbased denoising techniques, based on Bayesian leastsquares optimization...
Paul Scheunders, Steve De Backer
COGSR
2011
102views more  COGSR 2011»
15 years 1 months ago
Rethinking cognitive architecture via graphical models
Cognitive architectures need to resolve the diversity dilemma – i.e., to blend diversity and simplicity – in order to couple functionality and efficiency with integrability, e...
Paul S. Rosenbloom
ICIAP
2007
ACM
16 years 6 months ago
Sparseness Achievement in Hidden Markov Models
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
Manuele Bicego, Marco Cristani, Vittorio Murino
CIMCA
2005
IEEE
16 years 5 days ago
OntoBayes: An Ontology-Driven Uncertainty Model
— This paper describes an ontology-driven model, which integrates Bayesian Networks (BN) into the Ontology Web Language (OWL) to preserve the advantages of both. This model makes...
Yi Yang, Jacques Calmet
NIPS
2000
15 years 8 months ago
Sparse Representation for Gaussian Process Models
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
Lehel Csató, Manfred Opper