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A deep learning-based method to detect hot-spots in the visible video diagnostics of Wendelstein 7-X

MPS-Authors
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Biedermann,  C.       
Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society;

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Jakubowski,  M.       
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

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König,  R.       
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

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Krause,  M.
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

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Puig Sitjes,  A.       
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

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Citation

Szűcs, M., Szepesi, T., Biedermann, C., Cseh, G., Jakubowski, M., Kocsis, G., et al. (2022). A deep learning-based method to detect hot-spots in the visible video diagnostics of Wendelstein 7-X. Poster presented at 32nd Symposium on Fusion Technology (SOFT 2022), Dubrovnik, Virtual.


Cite as: https://hdl.handle.net/21.11116/0000-000B-2FB7-3
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