Using classifier-regressor pipeline in the problem of recognizing wavefront aberrations

This work proposes a method for increasing the accuracy of wavefront aberration recognition. The method involves the sequential use of two convolutional neural networks. The first neural network classifies the input point spread function (PSF) images according to the type of aberration. The second neural network performs the functions of a regressor, i.e. evaluates the values of the Zernike coeffi...