论文标题
用神经网络测量激光束
Measuring Laser Beams with a Neural Network
论文作者
论文摘要
深度神经网络（NN）用于同时检测图像中的激光束并测量其中心坐标，半径和角度方向。包含模拟激光束和具有实验激光束的图像的图像数据集，该图像使用空间光调节器生成，用于训练和评估NN。在模拟数据集上进行训练后，NN在实验数据集上实现了光束参数root-root-reserrors（RMSES）小于3.4％。随后对实验数据集的培训使RMSES降至1.1％以下。 NN方法可以用作光束参数的独立测量值，也可以通过提供精确的利益区域来补充其他梁分析方法。
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 rootmean-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.
