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Density Reconstruction from Noisy Radiographs using an Attention-based Transformer Network

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Abstract

A trained attention-based transformer network can robustly recover density fields from a sequence of features derived from radiographic images corrupted with blur, scatter, and noise. This approach is demonstrated on imploding shell hydrodynamic simulations.

© 2023 The Author(s)

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