Yuanqian Zhu

Augmentation-invariant Learning Strategy via Data Augmentation for Improving Model Generalization

Data augmentation is an effective technique for regularizing deep networks, which helps to enhance the generalizability and robustness of the model. However, in the field of medical imaging, traditional data augmentation techniques such as cropping, rotation, and degradation may inadvertently alter