Diffractive network-based single-pixel machine vision

We report a single-pixel machine vision framework based on deep learning-designed diffractive surfaces to perform a desired machine learning task. The object within the input field-of-view is illuminated with a broadband light source and the subsequent diffractive surfaces are trained to encode the spatial information of the object features onto the power spectrum of the diffracted light that is collected by a single-pixel detector in a single-shot. We experimentally demonstrated the all-optical inference capabilities of this single-pixel machine vision platform by classifying handwritten digits using 3D-printed diffractive layers and a plasmonic nanoantenna-based time-domain spectroscopy setup operating at THz wavelengths.