PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Recently artificial intelligent techniques such as deep learning (DL) have shown great potential in solving various inverse problems in computational imaging. In this presentation we will focus on the use of DL for computational imaging under certain extreme conditions. Three use cases will be discussed. Two out of the three are about the environment conditions such as imaging with extremely low light, and through very thick scattering media. The third one is about the neural network itself. We demonstrate that a neural network does not need to train at all before it can be used for some specific computational imaging tasks.