Deep Learning for Automated Quantification of Irradiation Defects in TEM Data: Relating Pixel-level Errors to Defect Properties.

Sainju, Rajat; Roberts, Graham; Chen, Wei-Ying; Hutchinson, Brian; Yang, Qian; Ding, Caiwen; Edwards, Danny J; Li, Meimei; Zhu, Yuanyuan.

Afiliação

Sainju R; Department of Materials Science and Engineering, University of Connecticut, Storrs, CT, USA.
Roberts G; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
Chen WY; Nuclear Science and Engineering Division, Argonne National Laboratory, Lemont, IL, USA.
Hutchinson B; Computer Science Department, Western Washington University, Bellingham, WA, USA.
Yang Q; National Security Directorate, AI and Data Analytics Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Ding C; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
Edwards DJ; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
Li M; Energy and Environment Directorate, Nuclear Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Zhu Y; Nuclear Science and Engineering Division, Argonne National Laboratory, Lemont, IL, USA.

Microsc Microanal ; 29(Supplement_1): 1559-1560, 2023 Jul 22.

Article em En | MEDLINE | ID: mdl-37613789

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article