Using deep learning to automatically generate design starting points for free-form imaging optical systems.

Fan C, Yang B, Liu Y, Zhao Q, Chen S, Qian B

DOI: 10.1364/ao.460977
Published: 2022 Jul 20
Container: Applied optics
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1364/ao.460977,
  title = {Using deep learning to automatically generate design starting points for free-form imaging optical systems.},
  author = {Fan C and Yang B and Liu Y and Zhao Q and Chen S and Qian B},
  year = {2022},
  journal = {Applied optics},
  doi = {10.1364/ao.460977},
  url = {https://doi.org/10.1364/ao.460977}
}

RIS

TY  - JOUR
TI  - Using deep learning to automatically generate design starting points for free-form imaging optical systems.
AU  - Fan C
AU  - Yang B
AU  - Liu Y
AU  - Zhao Q
AU  - Chen S
AU  - Qian B
PY  - 2022
JO  - Applied optics
DO  - 10.1364/ao.460977
UR  - https://doi.org/10.1364/ao.460977
ER  -

APA

C, F., B, Y., Y, L., Q, Z., S, C., & B, Q. (2022). Using deep learning to automatically generate design starting points for free-form imaging optical systems.. Applied optics. https://doi.org/10.1364/ao.460977

Source records

pubmed · retrieved 2026-09-24T20:01:56.214Z
europe-pmc · retrieved 2026-09-24T20:01:56.232Z