3D variational autoencoder for fingerprinting microstructure volume elements

Microstructure quantification is an important step towards establishing structure–property relationships in materials. Machine learning-based image processing methods have been shown to outperform conventional image processing techniques and are increasingly applied to microstructure quantification...

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Vydané v:	Computational materials science Ročník 259; s. 114145
Hlavní autori:	White, Michael D., Atkinson, Michael D., Plowman, Adam J., Shanthraj, Pratheek
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.09.2025
Predmet:	Crystal plasticity Feature learning Fingerprinting Machine learning Microstructure characterisation Surrogate model Microstructure characterisation Feature learning Crystal plasticity Fingerprinting Surrogate model Machine learning
ISSN:	0927-0256
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