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Found 5 papers, 1 papers with code
Nondestructive thermographic detection of internal defects using pixel-pattern based laser excitation and photothermal super resolution reconstruction
In this work, we present a novel approach to photothermal super resolution based thermographic resolution of internal defects using two-dimensional pixel pattern-based active photothermal laser heating in conjunction with subsequent numerical reconstruction to achieve a high-resolution reconstruction of internal defect structures.
Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating
Based on a combination of the application of special sampling strategies and a subsequent numerical optimization step in post-processing, thermographic super resolution has already proven to be superior to standard thermographic methods in the detection of one-dimensional defect/inhomogeneity structures.
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.
Classification of Spot-welded Joints in Laser Thermography Data using Convolutional Neural Networks
Spot welding is a crucial process step in various industries.
