Abstract
In recent years, artificial intelligence (AI) techniques have been developed rapidly. With the help of big data, massive parallel computing, and optimization algorithms, machine learning (ML) and (more recently) deep learning (DL) strategies have been equipped with enhanced learning and generalization capabilities. Besides becoming an essential framework in image and speech signal processing, AI has also been widely applied to solve several electromagnetic (EM) problems with unprecedented computational efficiency, including inverse scattering (IS) and EM imaging. In this article, a review of the most recent progresses in the application of ML and DL for such problems is given. We humbly hope a brief summary could help us better understand the pros and cons of this research topic and foster future research in using AI to address paramount challenges in the field of EM vision.
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