Phys.org  March 29, 2021 To mitigate the shortcomings and inefficiencies of traditional machine vision systems researchers at UCLA leveraged deep learning to design optical networks created by successive diffractive surfaces to perform computation and statistical inference as the input light passes through specially designed and 3D-fabricated layers. The diffractive optical networks are designed to process the incoming light at selected wavelengths with the goal of extracting and encoding the spatial features of an input object onto the spectrum of the diffracted light, which is collected by a single-pixel detector. Different object types or classes of data are assigned to different […]