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Quantifying microstructures of Earth materials using higher-order spatial correlations and deep generative adversarial networks
[post]
2022
unpublished
Key to most subsurface processes is to determine how structural and topological features at small length scales, i.e., the microstructure, control the effective and macroscopic properties of earth materials. Recent progress in imaging technology has enabled us to visualise and characterise microstructures at different length scales and dimensions. However, one limitation of these technologies is the trade-off between resolution and sample size (or representativeness). A promising approach to
doi:10.21203/rs.3.rs-2128261/v1
fatcat:ugw5x2wfbrct3hoqj4ombmvxny