A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram

Bellos, D.; Basham, M.; Pridmore, T.; French, A.P.

doi:10.1107/S1600577519003448

Journal of Synchrotron Radiation Journal of
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Figure 7
The training (A) and validation (B) PSNR graphs for the cubic interpolation (CI), the UDNN, the UDNN using 128–64 feature maps (UDNN-128) and the one using 32–16 (UDNN-32). The graphs depict the PSNR score from the initial 32400 backpropagations; after this point the network has converged and the PSNR score plateaus.

JOURNAL OF
SYNCHROTRON
RADIATION

ISSN: 1600-5775

Volume 26| Part 3| May 2019| Pages 839-853

https://doi.org/10.1107/S1600577519003448

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