Experimental data for evaluation of deep learning approach for high-accuracy electron counting of MAPS-type direct electron detectors

Experimental data of Celeritas XS direct detector for evaluation of deep learning counting approach as well as conventional connected component labeling counting and integrating. The dataset contains uniformly illuminated data with and without beam stop for MTF/DQE/DCE calculation, 4DSTEM datasets of monolayer WS2 before and after counting, and 4DSTEM datasets of SrTiO3[100] before and after counting. The zspy files can be loaded using Hyperspy(https://hyperspy.org)

本数据集为Celeritas XS型直接探测器的实验数据，用于评估深度学习计数方法，以及传统连通分量标记(connected component labeling)计数与积分方法。数据集涵盖带束流阻挡器(beam stop)与不带束流阻挡器的均匀照明数据，用于调制传递函数(MTF)、量子检测效率(DQE)及检测对比度效率(DCE)的计算；同时包含单层二硫化钨(WS₂)在计数前后的四维扫描透射电子显微镜(4DSTEM)数据集，以及钛酸锶[100]晶向(SrTiO₃[100])在计数前后的四维扫描透射电子显微镜数据集。该数据集内的zspy格式文件可通过Hyperspy（https://hyperspy.org）加载。