Deep-XFCT: Deep Learning 3D-Mineral Liberation Analysis with Micro-X-ray Fluorescence and Computed Tomography

Deep-XFCT: Deep Learning 3D-Mineral Liberation Analysis with Micro-X-ray Fluorescence and Computed Tomography

Quantitative characterisation through mineral liberation analysis is required for effective minerals processing in areas such as mineral deposits, tailings and reservoirs in industries for resources, environment and materials science. Current practices in mineral liberation analysis are based on 2D...

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Bibliographic Details
Main Authors: Patrick Kin Man Tung, Amalia Yunita Halim, Huixin Wang, Anne Rich, Christopher Marjo, Klaus Regenauer-Lieb
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Energies
Subjects:
deep learning segmentation
mineral liberation analysis
computed tomography
X-ray fluorescence
correlative microscopy
Online Access:https://www.mdpi.com/1996-1073/15/15/5326

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https://www.mdpi.com/1996-1073/15/15/5326

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