Deep learning for multiphase segmentation of X-ray images of gas diffusion layers
High-resolution X-ray computed tomography (micro-CT) has been widely used to
characterise fluid flow in porous media for different applications, including in gas diffusion …
characterise fluid flow in porous media for different applications, including in gas diffusion …
Using Machine Learning Algorithms for Water Segmentation in Gas Diffusion Layers of Polymer Electrolyte Fuel Cells
AD Shum, CP Liu, WH Lim, DY Parkinson… - Transport in Porous …, 2022 - Springer
X-ray computed tomography (CT) is increasingly used to characterize the morphology of
water distribution in gas diffusion layers (GDLs) for polymer electrolyte fuel cell (PEFC) …
water distribution in gas diffusion layers (GDLs) for polymer electrolyte fuel cell (PEFC) …
Segmentation of two-phase flow X-ray tomography images to determine contact angle using deep autoencoders
This study improves the characterization of in situ contact angles in porous media by
employing deep learning techniques (SegNet, UNet, ResNet, and UResNet) for multiphase …
employing deep learning techniques (SegNet, UNet, ResNet, and UResNet) for multiphase …
Integrating machine/deep learning methods and filtering techniques for reliable mineral phase segmentation of 3D X-ray computed tomography images
P Asadi, LE Beckingham - Energies, 2021 - mdpi.com
X-ray CT imaging provides a 3D view of a sample and is a powerful tool for investigating the
internal features of porous rock. Reliable phase segmentation in these images is highly …
internal features of porous rock. Reliable phase segmentation in these images is highly …
Three‐dimensional multiphase segmentation of X‐ray CT data of porous materials using a Bayesian Markov random field framework
Advancements in noninvasive imaging methods such as X‐ray computed tomography (CT)
have led to a recent surge of applications in porous media research with objectives ranging …
have led to a recent surge of applications in porous media research with objectives ranging …
Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM
Abstract Three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely
used in petroleum engineering because it can provide detailed pore structural information …
used in petroleum engineering because it can provide detailed pore structural information …
Deep learning for full-feature X-ray microcomputed tomography segmentation of proton electron membrane fuel cells
This study demonstrates the benefit of convolutional neural networks to accurately classify
the different materials of proton exchange membrane fuel cells using X-ray micro-computed …
the different materials of proton exchange membrane fuel cells using X-ray micro-computed …
Physical accuracy of deep neural networks for 2d and 3d multi-mineral segmentation of rock micro-ct images
Segmentation of 3D micro-Computed Tomographic uCT) images of rock samples is
essential for further Digital Rock Physics (DRP) analysis, however, conventional methods …
essential for further Digital Rock Physics (DRP) analysis, however, conventional methods …
Synthetic data generation for automatic segmentation of X-ray computed tomography reconstructions of complex microstructures
A Tsamos, S Evsevleev, R Fioresi, F Faglioni… - Journal of …, 2023 - mdpi.com
The greatest challenge when using deep convolutional neural networks (DCNNs) for
automatic segmentation of microstructural X-ray computed tomography (XCT) data is the …
automatic segmentation of microstructural X-ray computed tomography (XCT) data is the …
PoreSeg: An unsupervised and interactive-based framework for automatic segmentation of X-ray tomography of porous materials
X-ray imaging technology has seen immense progress in extracting the internal structure of
geomaterials, but the segmentation of images into voids and solids has remained a …
geomaterials, but the segmentation of images into voids and solids has remained a …