Image-based Data on Strain Fields of Microstructures with Porosity Defects_2

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 data contains image data of two sets of 10 microstructures with circular porosity defects and their strain fields, for each of the two experiments described in the aforementioned research article.本数据集是投稿至《计算材料科学期刊》（Computational Material Science Journal）的研究论文《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。该数据集是与上述论文一同提交至《计算材料科学期刊》的《数据简报》（Data in Brief）配套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），其中包含以二维数组形式表示的微结构图像及其对应的应变场数据。本数据集用于训练卷积神经网络（convolutional neural network），通过图像着色算法预测微结构内部的应变场。针对上述研究论文中描述的两项实验，本数据集为每项实验均包含两组各10张带有圆形孔隙缺陷的微结构图像及其对应的应变场数据。