Deep learning-based process for the automatic detection, tracking, and classification of thermal events on the in-vessel components of fusion reactors-Reference-Cited by-同舟云学术

Deep learning-based process for the automatic detection, tracking, and classification of thermal events on the in-vessel components of fusion reactors

Published:2023-07 Issue: Volume:192 Page:113636
ISSN:0920-3796
Container-title:Fusion Engineering and Design
language:en
Short-container-title:Fusion Engineering and Design

Author:

Grelier Erwan^ORCID,Mitteau Raphaël,Moncada Victor

Funder

EUROfusion Consortium Research Institutions

European Commission

Publisher

Elsevier BV

Subject

Mechanical Engineering,General Materials Science,Nuclear Energy and Engineering,Civil and Structural Engineering

Reference8 articles.

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2. Full coverage infrared thermography diagnostic for WEST machine protection;Courtois;Fusion Eng. Des.,2019

3. Deep learning and image processing for the automated analysis of thermal events on the first wall and divertor of fusion reactors;Grelier;Plasma Phys. Controlled Fusion,2022

4. Faster R-CNN: towards real-time object detection with region proposal networks;Ren,2015

5. Wu et al. (2019). Detectron2.

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