Accelerating Optimization Algorithms With Dynamic Parameter Selections Using Convolutional Neural Networks For Inverse Problems In Image Processing

7 Feb 2019Byung Hyun LeeSe Young Chun

Recent advances using deep neural networks (DNNs) for solving inverse problems in image processing have significantly outperformed conventional optimization algorithm based methods. Most works train DNNs to learn 1) forward models and image priors implicitly for direct mappings from given measurements to solutions, 2) data-driven priors as proximal operators in conventional iterative algorithms, or 3) forward models, priors and/or static stepsizes in unfolded structures of optimization iterations... (read more)

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