TY - JOUR N2 - Optical vortices are getting attention in modern optical metrology. Because of their unique features, they can be used as precise position markers. In this paper, we show that an artificial neural network can be used to improve vortex localization. A deep neural network with several hidden layers was trained to find subpixel vortex positions on the spiral phase maps. Several thousand training samples, differing by spiral density, its orientation, and vortex position, were generated numerically for teaching purposes. As a result, Best Validation Performance of the order of 10��5 pixel has been reached. To verify the usefulness of the proposed method, a related experiment in the setup of an optical vortex scanning microscope has been reported. It is shown that the vortex can be localized with subpixel accuracy also on experimental phase maps. L1 - http://journals.pan.pl/Content/120619/art06_i.pdf L2 - http://journals.pan.pl/Content/120619 PY - 2021 IS - No 3 EP - 508 DO - 10.24425/mms.2021.137131 KW - optical vortex KW - spiral phase map KW - pseudo phase KW - deep learning KW - neural network A1 - Popiołek-Masajada, Agnieszka A1 - Frączek, Ewa A1 - Burnecka, Emilia PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation VL - vol. 28 DA - 2021.09.06 T1 - Subpixel localization of optical vortices using artificial neural networks SP - 497 UR - http://journals.pan.pl/dlibra/publication/edition/120619 T2 - Metrology and Measurement Systems ER -