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ICIP
2007
IEEE
14 years 1 months ago
Locally Competitive Algorithms for Sparse Approximation
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficie...
Christopher J. Rozell, Don H. Johnson, Richard G. ...
ECCV
2010
Springer
13 years 12 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
ISBI
2007
IEEE
14 years 1 months ago
Inverse Biomedical Imaging Using Separately Adapted Meshes for Parameters and Forward Model Variables
Many important existing and upcoming biomedical imaging modalities lead to nonlinear relationships between state variables from which measurements result and the tissue properties...
Wolfgang Bangerth, Amit Joshi, Eva M. Sevick-Murac...
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 7 months ago
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
Joseph Shtok, Michael Zibulevsky, Michael Elad
ACIVS
2008
Springer
14 years 1 months ago
Scene Reconstruction Using MRF Optimization with Image Content Adaptive Energy Functions
Multi-view scene reconstruction from multiple uncalibrated images can be solved by two stages of processing: first, a sparse reconstruction using Structure From Motion (SFM), and ...
Ping Li, Rene Klein Gunnewiek, Peter H. N. de With