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Found 3 papers, 1 papers with code
A physics-informed neural network framework for modeling obstacle-related equations
Deep learning has been highly successful in some applications.
Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging
Photothermal imaging is a well-known technique in active thermography for nondestructive inspection of defects in materials such as metals or composites.
Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging
More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters.
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