| Issue |
BIO Web Conf.
Volume 129, 2024
The 17th European Microscopy Congress (EMC 2024)
|
|
|---|---|---|
| Article Number | 27004 | |
| Number of page(s) | 2 | |
| Section | Geological Materials and Bio-Mineral Systems | |
| DOI | https://doi.org/10.1051/bioconf/202412927004 | |
| Published online | 17 October 2024 | |
Deep learning 3D-mineral liberation analysis with micro-X-ray fluorescence, micro-computed tomography, and deep learning segmentation
1 Mark Wainwright Analytical Centre (MWAC), University of New South Wales, UNSW Sydney, Australia
2 Research Technology Services, University of New South Wales, UNSW Sydney, Australia
3 Mineral Resources, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Kensington, Australia
4 WA School of Mines: Minerals, Energy and Chemical Engineering, Australian Resources Research Centre (ARRC), Curtin University, Kensington, Australia
This article has no abstract.
Key words: Deep learning / Image analysis / Multi-modal
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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