0564063 - ÚFP 2023 RIV GB eng J - Journal Article
Zorek, M. - Škvára, V. - Smidl, L. - Pevný, T. - Seidl, Jakub - Grover, Ondřej
Semi-supervised deep networks for plasma state identification.
Plasma Physics and Controlled Fusion. Roč. 64, č. 12 (2022), č. článku 125004. ISSN 0741-3335. E-ISSN 1361-6587
R&D Projects: GA MŠMT(CZ) LM2018117; GA ČR(CZ) GA19-15229S
Institutional support: RVO:61389021
Keywords : plasma * neural networks * semi-supervised learning * classification
OECD category: Fluids and plasma physics (including surface physics)
Impact factor: 2.2, year: 2022
Method of publishing: Limited access
https://iopscience.iop.org/article/10.1088/1361-6587/ac9926
Permanent Link: https://hdl.handle.net/11104/0341367
Zorek, M. - Škvára, V. - Smidl, L. - Pevný, T. - Seidl, Jakub - Grover, Ondřej
Semi-supervised deep networks for plasma state identification.
Plasma Physics and Controlled Fusion. Roč. 64, č. 12 (2022), č. článku 125004. ISSN 0741-3335. E-ISSN 1361-6587
R&D Projects: GA MŠMT(CZ) LM2018117; GA ČR(CZ) GA19-15229S
Institutional support: RVO:61389021
Keywords : plasma * neural networks * semi-supervised learning * classification
OECD category: Fluids and plasma physics (including surface physics)
Impact factor: 2.2, year: 2022
Method of publishing: Limited access
https://iopscience.iop.org/article/10.1088/1361-6587/ac9926
Permanent Link: https://hdl.handle.net/11104/0341367