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PAMI
2006
126views more  PAMI 2006»
15 years 7 months ago
Estimation of Nonlinear Errors-in-Variables Models for Computer Vision Applications
In an errors-in-variables (EIV) model, all the measurements are corrupted by noise. The class of EIV models with constraints separable into the product of two nonlinear functions, ...
Bogdan Matei, Peter Meer
JSA
2007
84views more  JSA 2007»
15 years 7 months ago
Optimizing data structures at the modeling level in embedded multimedia
Traditional design techniques for embedded systems apply transformations on the source code to optimize hardwarerelated cost factors. Unfortunately, such transformations cannot ad...
Marijn Temmerman, Edgar G. Daylight, Francky Catth...
CSL
2002
Springer
15 years 7 months ago
Transformation streams and the HMM error model
The most popular model used in automatic speech recognition is the hidden Markov model (HMM). Though good performance has been obtained with such models there are well known limit...
M. J. F. Gales
IJCNN
2007
IEEE
16 years 1 months ago
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters
— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...
Il Park, António R. C. Paiva, Jose C. Princ...
ICASSP
2011
IEEE
14 years 11 months ago
Sparsity-based Sinogram Denoising for low-dose Computed Tomography
We propose a sinogram restoration method which consists of a patch-wise non-linear processing, based on a sparsity prior in terms of a learned dictionary. An off-line learning pro...
Joseph Shtok, Michael Elad, Michael Zibulevsky