基于深度学习设计表面的特定类别衍射相机。

Class-specific diffractive cameras based on deep learning-designed surfaces.

作者信息

Zhou Xuxi, Wang Shuming

机构信息

National Laboratory of Solid-State Microstructures, School of Physics, Nanjing University, Nanjing, 210093, China.

出版信息

Light Sci Appl. 2022 Sep 29;11(1):283. doi: 10.1038/s41377-022-00974-7.

DOI:10.1038/s41377-022-00974-7

PMID:36175397

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9522863/

Abstract

Recently, a new diffractive camera design based on transmissive surfaces structured using deep learning is proposed. It performs class-specific imaging of target objects and all-optical deletion of other classes of objects, which will promote the development of privacy-preserving digital cameras and mission-specific data.

摘要

最近，一种基于深度学习构建的透射表面的新型衍射相机设计被提出。它对目标物体进行特定类别的成像，并对其他类别的物体进行全光删除，这将推动隐私保护数字相机和特定任务数据的发展。