Abstract
A challenging problem in industrial radiography is accurate density reconstructions from X-ray projections corrupted by noise, scatter, etc. We propose a deep learning-based framework to extract robust features from radiographs and reconstruct the underlying densities.
© 2023 The Author(s)
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