Generation of highly realistic microstructural images of alloys from limited data with a style-based generative adversarial network | 研究者総覧SAMURAI - 物質・材料研究機構 (NIMS)

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Generation of highly realistic microstructural images of alloys from limited data with a style-based generative adversarial network

Guillaume Lambard, Kazuhiko Yamazaki, Masahiko Demura.

Scientific Reports 13 [1] 566. 2023.

https://doi.org/10.1038/s41598-023-27574-8

Open Access Springer Science and Business Media LLC (Publisher)

NIMS著者

Materials Data Repository (MDR)上の本文・データセット

作成時刻: 2023-01-18 03:34:13 +0900 更新時刻: 2026-09-29 08:41:49 +0900

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