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Generative adversarial networks with Monte Carlo dropout uncertainty quantification for structural health monitoring: Fibre Bragg grating data augmentation comparison in Hawk T1A aircraft

The signal generation capabilities of a novel data augmentation framework are examined in aerospace structures. First, the framework learns class-conditional temporal and spectral characteristics of the measured structural responses.

By Alvaro Peiro, Marios ImpraimakisarXiv cs.LG

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Originally published by arXiv cs.LG on Oct 19, 2026.

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