Topological Charge Estimation of Vortex Beams Based on Convolutional Neural Network
In this study,a method based on the convolutional neural network is developed to estimate the topological charge of vortex beams affected by astigmatic lenses.Vortex beams with different topological charges are incident on lenses with different astigmatism coefficients.The generated diffraction intensity images are input into six classical neural network models,which are VGG,AlexNet,ResNet-18,ResNet-34,ResNet-50,and Xception.Specificity,precision,recall,F1-score,and accuracy are used as evaluation functions to measure the topological charge estimated by the network model.The network models are used to estimate the topological charge of the entire and part intensity images.The results show that the proposed method is effective for estimating the topological charge.The VGG model exhibits the best performance in this task,and the accuracy of topological charge estimation is more than 99%.Therefore,it is feasible to use neural network to estimate the different topological charges carried by the vortex beams after passing through the lens with astigmatism.This method can be further applied in the feature recognition of beam transmission through optical systems.
NETL
NSTL
万方数据
