Enlarge the Error Prediction Dataset in 3-D Printing: An Unsupervised Dental Crown Mesh Generator

The quality of the dataset is critical to the performance of neural networks for error prediction in 3-D printing. In order to enlarge the dataset, we propose a customized two-stage framework, cascaded cross-modality generative adversarial networks (CCMGANs), for generating dental crown meshes in an...

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