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

Szűcs, M.; Szepesi, T.; Biedermann, C.; Cseh, G.; Jakubowski, M.; Kocsis, G.; König, R.; Krause, M.; Puig Sitjes, A.

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

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.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000B-2FB7-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-2FB8-2

Genre: Poster

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Creators:
Szűcs, M.¹, Author
Szepesi, T.¹, Author
Biedermann, C.², Author
Cseh, G.¹, Author
Jakubowski, M.³, Author
Kocsis, G.¹, Author
König, R.³, Author
Krause, M.³, Author
Puig Sitjes, A.³, Author

Affiliations:
1External Organizations, ou_persistent22
2Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society, ou_2040305
3Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856286

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Language(s): eng - English

Dates: Submitted: 2022

Publication Status: Submitted

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Title: 32nd Symposium on Fusion Technology (SOFT 2022)

Place of Event: Dubrovnik, Virtual

Start-/End Date: 2022-09-18 - 2022-09-23

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