The concept of deep diffractive neural networks (D2NN) was introduced by Professor Ozcan's research team in 2018. D2NN combines the principles of light diffraction with the functionalities of neural networks. It consists of a series of continuous diffractive layers. As light passes through these layers, variations in transmission or reflection coefficients at different positions cause changes in the light's phase and amplitude.
