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:
-
Applied Optics
- Pub Date:
- March 2022
- DOI:
- 10.1364/AO.443531
- arXiv:
- arXiv:2202.07801
- Bibcode:
- 2022ApOpt..61.1924H
- Keywords:
-
- Physics - Optics;
- Physics - Instrumentation and Detectors
- E-Print:
- 6 pages, 4 figures