Deep Learning With Mixup Augmentation For Improved Pore Detection During Additive Manufacturing

This article discusses the use of machine learning to predict process defects in additive manufacturing. The authors propose a data augmentation technique called Mixup to improve the accuracy of the ML models, which are trained on imbalanced and sparse datasets. The results show a significant increase in performance when using Mixup, with an accuracy of 99% on test datasets.