Browsing Electrical Engineering (EE) by Subject "Computational Imaging"
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Robust Non-convex Penalties for Solving Sparse Linear Inverse Problems and Applications to Computational Imaging
Sparse linear inverse problems require the solution to the l-0-regularized least-squares cost, which is not computationally tractable. Approximate and computationally tractable solutions are obtained by employing ... -
Tight Frames, Non-convex Regularizers, and Quantized Neural Networks for Solving Linear Inverse Problems
The recovery of a signal/image from compressed measurements involves formulating an optimization problem and solving it using an efficient algorithm. The optimization objective involves data fidelity, which is responsible ...