上海科技大学知识管理系统

A computer-implemented method is provided. The method includes obtaining a plurality of images representing projections of an object placed in a plurality of poses and a plurality of translations; assigning a pose embedding vector, a flow embedding vector and a contrast transfer function (CTF) embedding vector to each image; encoding, by a computer device, a machine learning model comprising a pose network, a flow network, a density network and a CTF network; training the machine learning model using the plurality of images; and reconstructing a 3D structure of the object based on the trained machine learning module.

提供了一种计算机实现的方法。 所述方法包含获得表示以多个姿态和多个平移放置的对象的投影的多个图像； 将姿态嵌入向量、流嵌入向量和对比度传递函数(CTF)嵌入向量分配给每个图像; 由计算机装置编码机器学习模型，所述机器学习模型包括姿态网络、流网络、密度网络和CTF网络； 使用所述多个图像来训练所述机器学习模型； 以及基于所述经训练机器学习模块来重建所述对象的3D结构。