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. ...
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...
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...
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...
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