Composite Microstructures Dataset

该数据集包含了通过特定算法生成的二维复合微结构图像，该算法基于随机序列吸附（RSA）技术。这些图像旨在用于预测材料的力学性能，包括杨氏模量和屈服强度。该数据集规模宏大，包含7,893张图像，其中纤维体积分数从20.0%到44.0%不等。其任务是利用卷积神经网络（CNNs）对复合材料的力学性能进行预测。

This dataset contains two-dimensional composite microstructure images generated by a specific algorithm based on the random sequential adsorption (RSA) technique. These images are intended for predicting the mechanical properties of materials, including Young's modulus and yield strength. This large-scale dataset consists of 7,893 images, with fiber volume fractions ranging from 20.0% to 44.0%. The task associated with this dataset is to use convolutional neural networks (CNNs) to predict the mechanical properties of composite materials.