Dataset for "Machine learning-based classification of vector vortex beams"

Source code and data for the paper: Taira Giordani, Alessia Suprano, Emanuele Polino, Francesca Acanfora, Luca Innocenti, Alessandro Ferraro, Mauro Paternostro, Nicoló Spagnolo, and Fabio Sciarrino, Machine learning-based classification of vector vortex beams, Phys. Rev. Lett. 124, 160401, (2020). Content: Notebooks: Jupyer notebooks containing code and explanations to reproduce the results of the paper. src. The notebooks use a number of supporting functions, which are all defined here. Data: Contains the datasets used in the notebooks. Saved_CNN_models. Pre-trained CNNs used in the notebooks.本数据集包含论文《基于机器学习的矢量涡旋光束分类（Machine learning-based classification of vector vortex beams）》的源代码与相关数据，论文作者为Taira Giordani、Alessia Suprano、Emanuele Polino、Francesca Acanfora、Luca Innocenti、Alessandro Ferraro、Mauro Paternostro、Nicolò Spagnolo及Fabio Sciarrino，发表于《物理评论快报（Phys. Rev. Lett.）》124卷，160401页（2020年）。 具体内容如下： Notebooks：Jupyter笔记本，内含可复现论文研究结果的代码与详细说明文档。 src：存放该笔记本所依赖的全部辅助函数。 Data：存储笔记本中使用的所有数据集。 Saved_CNN_models：存放笔记本中用到的预训练卷积神经网络（Convolutional Neural Network, CNN）模型。