Journal article
Measuring laser beams with a neural network
- Abstract:
- A deep neural network (NN) is used to simultaneously detect laser beams in images and measure their center coordinates, radii, and angular orientations. A dataset of images containing simulated laser beams and a dataset of images with experimental laser beams—generated using a spatial light modulator—are used to train and evaluate the NN. After training on the simulated dataset the NN achieves beam parameter root mean square errors (RMSEs) of less than 3.4% on the experimental dataset. Subsequent training on the experimental dataset causes the RMSEs to fall below 1.1%. The NN method can be used as a stand-alone measurement of the beam parameters or can compliment other beam profiling methods by providing an accurate region-of-interest.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 2.6MB, Terms of use)
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- Publisher copy:
- 10.1364/AO.443531
Authors
- Publisher:
- Optica Publishing Group
- Journal:
- Applied Optics More from this journal
- Volume:
- 61
- Issue:
- 8
- Pages:
- 1924-1929
- Publication date:
- 2022-03-02
- Acceptance date:
- 2022-02-04
- DOI:
- EISSN:
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2155-3165
- ISSN:
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1559-128X
- Pmid:
-
35297883
- Language:
-
English
- Keywords:
- Pubs id:
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1244087
- Local pid:
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pubs:1244087
- Deposit date:
-
2022-04-22
Terms of use
- Copyright holder:
- Optica Publishing Group
- Copyright date:
- 2022
- Rights statement:
- © 2022 Optica Publishing Group.
- Notes:
-
This is the accepted manuscript version of the article. The final version is available from Optica Publishing Group at https://doi.org/10.1364/AO.443531
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