In this work, a novel technique is proposed that combines the Born iterative method, based
on a quadratic programming approach, with convolutional neural networks to solve the ill …

The application and comparison of U-Net convolutional neural network architectures is
proposed in this work to guarantee a fast and accurate convergence of inverse scattering …

An improved machine learning approach is presented in this paper to guarantee the fast
convergence of the Born Iterative Method, even in the presence of strong scatterers, by …

This study discusses a new technique based on the Born iterative method, with a quadratic
programming approach, which uses convolutional neural networks to solve microwave …

The multi-objective integer programming problem often occurs in multi-criteria decision-
making situations, where the decision variables are integers. In the present paper, we have …

In clinical settings, computed tomography (CT), magnetic resonance imaging (MRI), or
positron emission tomography (PET) are commonly employed in brain imaging to assist …

Generalized Method of Lagrange Multipliers: A Robust Optimization Strategy for Microwave
Tomography Page 1 IEEE TRANSACTIONS ON MICROWAVE THEORY AND …

Based on the assumption that the pseudorandom characteristic of variational Born iterative
method (VBIM), the retrieved contrast parameter distribution in the discrete cells complies …

The challenging task of solving inverse scattering problems (ISPs) is due to their inherent ill-
posedness and nonlinearity. To alleviate ill-posedness, a novel hybrid regularization …

A robust hierarchical domain constraint (HDC) strategy is proposed for the multiscale
contrast objects reconstruction in this letter. The Monte Carlo method and point evaluation …