Characterization of high speed steels _ In situ experimental data and their evaluation supported by machine learning algorithms
Research output: Contribution to conference › Paper › 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. Paper presented at EUROMAT 2021, Graz (online), Austria.
2021. Paper presented at EUROMAT 2021, Graz (online), Austria.
Research output: Contribution to conference › Paper › 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', Paper presented at 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. Paper presented at 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. Paper presented at EUROMAT 2021, Graz (online), Austria.
Author
Bibtex - Download
@conference{4055232fd4ea404782d342d6239e332b,
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 Wiessner",
year = "2021",
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
Y1 - 2021
M3 - Paper
T2 - EUROMAT 2021
Y2 - 13 September 2021 through 17 September 2021
ER -
