Deep learning based distorted Born iterative method for improving microwave imaging
Author:
Affiliation:
1. Department of Electronics and Communication Engineering , National Institute of Technology , Ponda , Goa , India
Abstract
Funder
Core Research Grant, SERB
Publisher
Walter de Gruyter GmbH
Subject
Electrical and Electronic Engineering
Link
https://www.degruyter.com/document/doi/10.1515/freq-2023-0074/pdf
Reference20 articles.
1. N. Nikolova, Introduction to Microwave Imaging, United Kingdom, Cambridge University Press, 2017.
2. M. Pastorino, Microwave Imaging, Hoboken, NJ, John Wiley & Sons, 2010.
3. X. Chen, Computational Methods for Electromagnetic Inverse Scattering, Singapore, Wiley-IEEE press, 2018.
4. P. M. Berg and R. E. Kleinman, “A contrast source inversion method,” Inverse Probl., vol. 13, pp. 1607–1620, 1997, https://doi.org/10.1088/0266-5611/13/6/013.
5. W. Chew and Y. Wang, “Reconstruction of two-dimensional permittivity distribution using the distorted Born iterative method,” IEEE Trans. Med. Imaging, vol. 9, pp. 218–225, 1990, https://doi.org/10.1109/42.56334.
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