Detection of Thermal Events by Semi-Supervised Learning for Tokamak First Wall Safety

This article explores a semi-supervised object detection approach to detect thermal events on the internal wall of tokamaks. A huge amount of data is produced during an experimental campaign by the infrared (IR) viewing systems used to monitor the inner thermal shields during machine operation. The...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement 2024, Vol.73, p.1-9
Hauptverfasser:	Staron, Christian, Le Borgne, Herve, Mitteau, Raphael, Grelier, Erwan, Allezard, Nicolas
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Annotations Artificial intelligence Data models Datasets Deep learning Domain adaptation fusion reactor protection infrared (IR) thermography Machine learning Manuals object detection Object recognition Plasmas Semi-supervised learning semi-supervised learning (SSL) Semisupervised learning Tokamak devices
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