Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer

27 Jun 2020Qian LiQingyuan HuYong QiSaiyu QiJie MaJian Zhang

Data augmentation have been intensively used in training deep neural network to improve the generalization, whether in original space (e.g., image space) or representation space. Although being successful, the connection between the synthesized data and the original data is largely ignored in training, without considering the distribution information that the synthesized samples are surrounding the original sample in training... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.