3 papers
cond-mat.mtrl-sci2021
The Adoption of Image-Driven Machine Learning for Microstructure Characterization and Materials Design: A Perspective
Arun Baskaran, Elizabeth J. Kautz, Aritra Chowdhary +3
The recent surge in the adoption of machine learning techniques for materials design, discovery, and characterization has resulted in an increased interest and application of Image…
physics.app-ph2020
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships
Wufei Ma, Elizabeth Kautz, Arun Baskaran +4
We investigate methods of microstructure representation for the purpose of predicting processing condition from microstructure image data. A binary alloy (uranium-molybdenum) that…
physics.app-ph2019
An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction
Elizabeth Kautz, Wufei Ma, Saumyadeep Jana +4
Micrograph quantification is an essential component of several materials science studies. Machine learning methods, in particular convolutional neural networks, have previously dem…