Abstract Title: Deep Sensing: Jointly optimizing imaging and processing

Deep neural network (DNN) is a powerful tool for solving image processing and computer
vision tasks such as image and video reconstructions, object recognition, and scene
understanding, etc. However, DNN have been used for only the digital domain in the
imaging pipeline, such as the feature extractor and classifier models after an image is
captured and digitized. In this research, we propose a new framework called “deep
sensing.” The proposed framework also models the analog layer to the neural network
model and jointly optimizes the parameters in optics and sensor designs of a camera, as
well as reconstruction and classification models by the same training strategy.