Pages that link to "Item:Q1622858"
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The following pages link to Porous structure reconstruction using convolutional neural networks (Q1622858):
Displaying 17 items.
- 3D numerical reconstruction of well-connected porous structure of rock using fractal algorithms (Q1668396) (← links)
- Statistical characterization and reconstruction of heterogeneous microstructures using deep neural network (Q2020836) (← links)
- An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning (Q2021153) (← links)
- Reconstruction, optimization, and design of heterogeneous materials and media: basic principles, computational algorithms, and applications (Q2064257) (← links)
- Stochastic reconstruction of 3D microstructures from 2D cross-sectional images using machine learning-based characterization (Q2072752) (← links)
- 3D reconstruction of porous media using a batch normalized variational auto-encoder (Q2085099) (← links)
- Numerical modelling of reservoir at pore scale: a comprehensive review (Q2099732) (← links)
- Automated porosity estimation using CT-scans of extracted core data (Q2147571) (← links)
- A deep learning perspective on predicting permeability in porous media from network modeling to direct simulation (Q2192831) (← links)
- Geological facies recovery based on weighted \(\ell_1\)-regularization (Q2198925) (← links)
- 3D pore space reconstruction using deep residual deconvolution networks (Q2240947) (← links)
- A deep-learning-based geological parameterization for history matching complex models (Q2323494) (← links)
- Synchrotron radiation-based \(l_1\)-norm regularization on micro-CT imaging in shale structure analysis (Q2398391) (← links)
- Reconstruction of Three-Dimensional Porous Media: Statistical or Deep Learning Approach? (Q4553862) (← links)
- Stochastic reconstruction of porous media based on attention mechanisms and multi-stage generative adversarial network (Q6074263) (← links)
- Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network (Q6094706) (← links)
- Estimating permeability of 3D micro-CT images by physics-informed CNNs based on DNS (Q6106108) (← links)
