2022
DOI: 10.48550/arxiv.2205.12052
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On statistic alignment for domain adaptation in structural health monitoring

Abstract: The practical application of structural health monitoring (SHM) is often limited by the availability of labelled data. Transfer learning -specifically in the form of domain adaptation (DA) -gives rise to the possibility of leveraging information from a population of physical or numerical structures, by inferring a mapping that aligns the feature spaces. Typical DA methods rely on nonparametric distance metrics, which require sufficient data to perform density estimation. In addition, these methods can be prone… Show more

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