An attention-augmented CNN identifies tearing-mode magnetic islands in EAST tokamak ECE signals with 91.96% test accuracy, a modest gain over a plain CNN.
Disruptive neoclassical tearing mode seeding in DIII -D with implications for ITER
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Attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak
An attention-augmented CNN identifies tearing-mode magnetic islands in EAST tokamak ECE signals with 91.96% test accuracy, a modest gain over a plain CNN.