Deep-learning workflow for detecting slow slip events. (IMAGE)
Caption
Deep-learning workflow for detecting slow slip events. Continuous daily borehole strain observations (white curves) and their corresponding wavelet representations (background colors) from corrected strain components were used as input to the neural network. The red dashed box highlights a short-duration slow slip event recorded on 15 June 2013. The autoencoder with skip connections learns a compact latent representation of the input data, which is subsequently used for unsupervised clustering to distinguish deformation signals from non-deformation signals.
Credit
Zahra Zali, GFZ
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Credit must be given to the creator.
License
CC BY