Košík

0575308 - ÚPT 2024 GB eng A - Abstrakt
Čermák, Jan - Ambrož, Ondřej - Zouhar, Martin - Jozefovič, Patrik - Mikmeková, Šárka
Methodology for Collecting and Aligning Correlative SEM, CLSM and LOM Images of Bulk Material Microstructure to Create a Large Machine Learning Training Dataset.
Microscopy and Microanalysis. Cambridge University Press. Roč. 29, S1 (2023), s. 2016-2018. ISSN 1431-9276. E-ISSN 1435-8115.
[Microscopy & Microanalysis 2023. 23.07.2023-27.07.2023, Minneapolis]
Grant CEP: GA TA ČR(CZ) TN02000020
Grant ostatní: AV ČR(CZ) LQ100652201
Program: Prémie Lumina quaeruntur
Institucionální podpora: RVO:68081731
Klíčová slova: correlative microscopy * metalography * specimen navigation * image registration * machine learning dataset
Obor OECD: Materials engineering
https://academic.oup.com/mam/article/29/Supplement_1/2016/7228070
Trvalý link: https://hdl.handle.net/11104/0345091