Target counting and location detection in electromagnetics using convolutional neural networks

Abstract

Here, we showcase an application of neural networks (NNs) to solve an inverse problem in electromagnetics. Wires are randomly distributed into an area of known dimensions. The wires are then illuminated with a monochromatic plane wave (PW) at a certain angle of incidence, and the electromagnetic (EM) field measured at a finite number of points along the perimeter of the area is then fed into a convolutional neural network (CNN) designed to predict either (i) the number of the wires or (ii) the location of the wires.