301 citations · 343 across the 5 of their papers we have counts for
5 papers
Prediction of microstructural representativity from a single image
Amir Dahari, Ronan Docherty, Steve Kench +1
In this study, we present a method for predicting the representativity of the phase fraction observed in a single image (2D or 3D) of a material. Traditional approaches often requi…
Two approaches to inpainting microstructure with deep convolutional generative adversarial networks
Isaac Squires, Samuel J. Cooper, Amir Dahari +1
Imaging is critical to the characterisation of materials. However, even with careful sample preparation and microscope calibration, imaging techniques are often prone to defects an…
MicroLib: A library of 3D microstructures generated from 2D micrographs using SliceGAN
Steve Kench, Isaac Squires, Amir Dahari +1
3D microstructural datasets are commonly used to define the geometrical domains used in finite element modelling. This has proven a useful tool for understanding how complex materi…
Fusion of complementary 2D and 3D mesostructural datasets using generative adversarial networks
Amir Dahari, Steve Kench, Isaac Squires +1
Modelling the impact of a material's mesostructure on device level performance typically requires access to 3D image data containing all the relevant information to define the geom…
Generating 3D structures from a 2D slice with GAN-based dimensionality expansion
Steve Kench, Samuel J. Cooper
Generative adversarial networks (GANs) can be trained to generate 3D image data, which is useful for design optimisation. However, this conventionally requires 3D training data, wh…