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Sandstone rock tomographic data, i12 beamline, DLS synchrotron

<p>This data compliments a paper <i>Conditional generative adversarial networks for stripe artefact removal in high-resolution X-ray tomography </i>by D. Kazantsev, L. Beveridge, V. Shanmugasundar and O. Magdysyuk to be published in the <strong>Tomography of Materials and Structures</strong> journal in 2023 (to be updated). This data alongside the data from <a href="https://zenodo.org/records/1443568#.ZBREbUjP1qN">here</a> was used to train the network to remove stripe artefacts.&nbsp;</p><p>The code is written in Python and located at: https://github.com/dkazanc/NoStripesNet</p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
12
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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