Raman spectra contain abundant information from molecules but are difficult to analyze, especially for the mixtures. Deep-Learning-Based Components Identification for Raman Spectroscopy (DeepCID) has
利用Active contour 算法识别腹部脂肪像素点；对识别出的腹部脂肪像素点采用多尺度块作为特征输入，通过新的深度神经网络算法自动学习分层的抽象本质特征，将这些特征输入分类算法得到初步分割结果；然后将初步分割结果转到极坐标中，利用 SAT 在极坐标下成为图像底部的特征，得到腹部脂肪分割图；最后按照梯度高低对腹部脂肪分割图中各类型脂肪比例进行计算，并通过体绘制技术直观显示计算结果。
This folder contains formation energy of BDE-db,QM9,PC9,QMugs and QMugs1.1 datasets by filtered (The training, test, and validation sets were randomly split in a ratio of 0.8, 0.1, and 0.1, respective
