Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms
Research output: Contribution to conference › Presentation › Research › peer-review
Standard
Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms. / Gamsjäger, Ernst; Wießner, Manfred.
2021. EUROMAT 2021, Graz (online), Austria.
2021. EUROMAT 2021, Graz (online), Austria.
Research output: Contribution to conference › Presentation › Research › peer-review
Harvard
Gamsjäger, E & Wießner, M 2021, 'Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms', EUROMAT 2021, Graz (online), Austria, 13/09/21 - 17/09/21.
APA
Gamsjäger, E., & Wießner, M. (2021). Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms. EUROMAT 2021, Graz (online), Austria.
Vancouver
Gamsjäger E, Wießner M. Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms. 2021. EUROMAT 2021, Graz (online), Austria.
Author
Bibtex - Download
@conference{319fa11201f94bceb3c9f999b3c4f913,
title = "Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms",
author = "Ernst Gamsj{\"a}ger and Manfred Wie{\ss}ner",
year = "2021",
month = sep,
language = "English",
note = "EUROMAT 2021 ; Conference date: 13-09-2021 Through 17-09-2021",
}
RIS (suitable for import to EndNote) - Download
TY - CONF
T1 - Characterization of high speed steels – In-situ experimental data and their evaluation supported by machine learning algorithms
AU - Gamsjäger, Ernst
AU - Wießner, Manfred
PY - 2021/9
Y1 - 2021/9
M3 - Presentation
T2 - EUROMAT 2021
Y2 - 13 September 2021 through 17 September 2021
ER -
