Easy Batch Normalization
ITMO University（ITMO大学）；Artificial Intelligence Research Institute（人工智能研究所）；Tubingen Universitat（图宾根大学）
英文摘要：
It was shown that adversarial examples improve object recognition. But what about their opposite side, easy examples? Easy examples are samples that the machine learning model classifies correctly with high confidence. In our paper, we are making the first step toward exploring the potential benefits of using easy examples in the training procedure of neural networks. We propose to use an auxiliary batch normalization for easy examples for the standard and robust accuracy improvement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
