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Scalable Quality Assessment of Ground Motion Records Via Interpretable Deep Learning Architectures
Earthquake engineers rely on accurate recordings of ground shaking to design safe and resilient buildings. However, sorting through thousands of these recordings to find the reliable ones and throwing out those ruined by sensor errors or background noise is traditionally done by hand. Because modern
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