Image-based Data on Strain Fields of Microstructures with Porosity Defects_3

This dataset is one of the three datasets that are utilized in the research, 'Predicting elastic strain fields in defective microstructures using image colorization algorithms' submitted for publication in the Computational Material Science Journal. This is a part of supplementary data for the Data in Brief article co-submitted alongside the aforementioned paper in Computational Material Science Journal. The data file is a MATLAB Binary Data Compressed file (.mat) that contains images of microstructures and their respective strain fields represented as two-dimensional arrays. This data is utilized for training a convolutional neural network to predict strain fields within a microstructure, through image colorization algorithm. This dataset contains six sub-folders each having two datasets (500 samples and 50 samples) of microstructures with porosity defects of six unique shapes described in the aforementioned research article along with their strain fields.本数据集为已提交至《计算材料科学学报（Computational Materials Science Journal）》的研究《利用图像着色算法预测缺陷微结构中的弹性应变场》所使用的三个数据集之一。本数据集亦是与上述论文一同提交至该期刊的《数据简报（Data in Brief）》文章的补充数据的一部分。该数据文件为MATLAB二进制压缩数据文件（.mat），其中存储有微结构图像以及各自以二维数组形式表征的对应应变场。本数据集用于训练卷积神经网络，以通过图像着色算法实现微结构内应变场的预测。本数据集包含六个子文件夹，每个子文件夹均设有两组数据集（分别包含500个与50个样本），对应上述研究文章中提及的六种不同形状的孔隙缺陷微结构及其对应的应变场。