Estimating steel microstructures by deep learning framework combined with phase transformation model

Satoshi Noguchi

Presentation information

Oral Session

F. Functional & Structural » [F-1] Future prospect of DX-driven development in structural materials

[F1-O401] Oral 401

Thu. Dec 14, 2023 9:00 AM - 12:00 PM Session 13 (Room I)

Chair: Katsunari Oikawa (Tohoku Univ.), Kenji Nagata (National Institute for Materials Science)

11:20 AM - 11:40 AM

[F1-O401-06] Estimating steel microstructures by deep learning framework combined with phase transformation model

*Satoshi Noguchi¹, Syuji Aihara², Junya Inoue³ (1. Res. Inst. for Value-added Information Generation, Japan Agency for Marine-Earth Science and Technology (Japan), 2. The Univ. of Tokyo (Japan), 3. Department of Material Eng., The Univ. of Tokyo (Japan))

Keywords:Microstructure estimation, Deep learning, VQVAE, PixelCNN, Process–structure–property linkage

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