... the initial training process. We synthesize a semi-supervised learning framework, building upon the residual neural network (ResNet) as well as the deep convolutional generative adversarial network (DCGAN), to extract features from the ground truth data and synthetic data. The performance boost of synthetic...

... knowledge in the complete and accurate labeling of datasets. To address these challenges, a semi-supervised learning approach is proposed that makes use of partially labeled subsets. The proposed methodology is applied to high-dimensional in-process measurement data, utilizing a convolutional autoencoder...