Deep-Learning-Based Imaging through Glass-Air Disordered Fiber with Transverse Anderson Localization

We demonstrate for the first time that deep neural networks (DNNs) can be trained to recover images transported through a 90 cm-long silica-air disordered optical fiber at variable working distances without any distal optics.