FreeformNet: fast and automatic generation of multiple-solution freeform imaging systems enabled by deep learning

Boyu Mao; Tong Yang; Huiming Xu; Wenchen Chen; Dewen Cheng; Yongtian Wang

doi:10.1364/PRJ.492938

Photonics Research, Volume. 11, Issue 8, 1408(2023)

FreeformNet: fast and automatic generation of multiple-solution freeform imaging systems enabled by deep learning

Boyu Mao¹, Tong Yang^1,2、*, Huiming Xu¹, Wenchen Chen¹, Dewen Cheng^1,3, and Yongtian Wang^1,2

¹Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

²Beijing Key Laboratory of Advanced Optical Remote Sensing Technology, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

³e-mail: cdwlxk@bit.edu.cn

show less

Cited By

Article index updated: May. 2, 2024

Citation counts are provided from Web of Science. The counts may vary by service, and are reliant on the availability of their data.

The article is cited by 3 article(s) from Web of Science.

Tools

Get Citation

Copy Citation Text

Boyu Mao, Tong Yang, Huiming Xu, Wenchen Chen, Dewen Cheng, Yongtian Wang, "FreeformNet: fast and automatic generation of multiple-solution freeform imaging systems enabled by deep learning," Photonics Res. 11, 1408 (2023)

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Imaging Systems, Microscopy, and Displays

Received: Apr. 12, 2023

Accepted: Jun. 7, 2023

Published Online: Jul. 31, 2023

The Author Email: Tong Yang (yangtong@bit.edu.cn)

DOI:10.1364/PRJ.492938

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology