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» Learning to Generate Fast Signal Processing Implementations
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AIPR
2005
IEEE
14 years 1 months ago
Hyperspectral Detection Algorithms: Operational, Next Generation, on the Horizon
Abstract—The multi-band target detection algorithms implemented in hyperspectral imaging systems represent perhaps the most successful example of image fusion. A core suite of su...
A. Schaum
ICASSP
2011
IEEE
12 years 11 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
ICASSP
2010
IEEE
13 years 5 months ago
GHT based implementation of the expectation maximization for mixtures of multi-Gaussians and its applications to video tracking
In this work, the problem of the estimation of parameters in case of mixtures of models composed by the sum of multiple Gaussians is considered. It will be shown how this estimati...
Francesco Monti, Carlo S. Regazzoni
ICONIP
2009
13 years 5 months ago
Adaptive Sensor-Driven Neural Control for Learning in Walking Machines
Abstract. Wild rodents learn the danger-predicting meaning of predator bird calls through the paring of cues which are an aversive stimulus (immediate danger signal or unconditione...
Poramate Manoonpong, Florentin Wörgötter
ICASSP
2009
IEEE
14 years 2 months ago
Fast LCD motion deblurring by decimation and optimization
The LCD deblurring problem is considered as a simple bounded quadratic programming problem and is solved using conjugate gradient with early stopping criteria to avoid excessive s...
Stanley H. Chan, Truong Q. Nguyen