@inproceedings{32961e23a2c2427b93c88fa514cbeb03,
title = "Generating off-axis reflective imaging systems consisting of flat phase elements based on deep-learning",
abstract = "Imaging systems consisting of flat phase elements can achieve more compactness and lighter-weight. In this paper, we propose a design framework of off-axis reflective imaging system consisting of flat phase elements based on deep-learning. Differential ray tracing for off-axis systems consisting of flat phase elements is used. Supervised and unsupervised learning are combined to improve the generalization ability of the deep neural network for a wide range of system and structure parameter values. Single or multiple systems can be generated directly after the design requirements are inputted into the network, and can be taken as good starting points for further optimization. The design efficiency can be significantly improved, and the dependence on the advanced design skills is dramatically reduced.",
keywords = "Phase elements, deep learning, imaging system design, supervised learning, unsupervised learning",
author = "Boyu Mao and Tong Yang and Huiming Xu and Dewen Cheng and Yongtian Wang",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; Optical Design and Testing XIII 2023 ; Conference date: 14-10-2023 Through 15-10-2023",
year = "2023",
doi = "10.1117/12.2686762",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yongtian Wang and Kidger, {Tina E.} and Rengmao Wu",
booktitle = "Optical Design and Testing XIII",
address = "United States",
}