2023
DOI: 10.1109/tap.2023.3312818
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Deep Injective Prior for Inverse Scattering

AmirEhsan Khorashadizadeh,
Vahid Khorashadizadeh,
Sepehr Eskandari
et al.

Abstract: In electromagnetic inverse scattering, the goal is to reconstruct object permittivity using scattered waves. While deep learning has shown promise as an alternative to iterative solvers, it is primarily used in supervised frameworks which are sensitive to distribution drift of the scattered fields, common in practice. Moreover, these methods typically provide a single estimate of the permittivity pattern, which may be inadequate or misleading due to noise and the ill-posedness of the problem. In this paper, we… Show more

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