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Article overview
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Accelerating Neutron Scattering Data Collection and Experiments Using AI Deep Super-Resolution Learning | | Ming-Ching Chang
; Yi Wei
; Wei-Ren Chen
; Changwoo Do
; | | Date: |
17 Apr 2019 | | Abstract: | We present a novel methodology of augmenting the scattering data measured by
small angle neutron scattering via an emerging deep convolutional neural
network (CNN) that is widely used in artificial intelligence (AI). Data
collection time is reduced by increasing the size of binning of the detector
pixels at the sacrifice of resolution. High-resolution scattering data is then
reconstructed by using AI deep super-resolution learning method. This technique
can not only improve the productivity of neutron scattering instruments by
speeding up the experimental workflow but also enable capturing kinetic changes
and transient phenomenon of materials that are currently inaccessible by
existing neutron scattering techniques. | | Source: | arXiv, 1904.8450 | | Services: | Forum | Review | PDF | Favorites | |
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