Deep Learning with Attention Mechanism for Electromagnetic Inverse Scattering

In this paper, a new deep learning technique is investigated to improve the solution of electromagnetic inverse scattering problems (ISPs). The basic idea of this technique is to introduce the attention mechanism to U-Net. By doing this, the deep learning model can automatically learn to focus on target areas of the measured scattered field matrix. In this way, the proposed technique can offer higher accuracy and faster convergence compared with the traditional deep learning networks. Numerical results validate the efficacy of the proposed technique.