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arXiv · 2302.11259

Transfer Learning Enhanced Full Waveform Inversion

Stefan Kollmannsberger·Divya Singh·Leon Herrmann
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Abstract

We propose a way to favorably employ neural networks in the field of non-destructive testing using Full Waveform Inversion (FWI). The presented methodology discretizes the unknown material distribution in the domain with a neural network within an adjoint optimization. To further increase efficiency of the FWI, pretrained neural networks are used to provide a good starting point for the inversion. This reduces the number of iterations in the Full Waveform Inversion for specific, yet generalizable settings.

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BibTeXRIS

Stefan Kollmannsberger, Divya Singh, Leon Herrmann. 2023-02-22. Transfer Learning Enhanced Full Waveform Inversion. https://doi.org/10.1109/aim46323.2023.10196158

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