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NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION

Software ·
DOI:https://doi.org/10.11578/dc.20210819.7· OSTI ID:code-62502 · Code ID:62502
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A deep neural network model plus automatic differentiation is developed for retrieving phase information from 3D coherent diffraction images. The model is implemented using Tensorflow and the training dataset is generated using physics-based atomistic simulations. Custom codes are written to handle the resampling of diffraction images to oversampling ratios appropriate for the neural network model.

Software Type:
Scientific
License(s):
BSD 3-clause "New" or "Revised" License
Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
US DOE BES ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING; ARGONNE LDRD
Primary Award/Contract Number:
AC02-06CH11357
DOE Contract Number:
AC02-06CH11357
Code ID:
62502
OSTI ID:
code-62502
Country of Origin:
United States

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