摘要
1 Introduction.Recently,some research efforts[1]have tried to combine selfsupervised learning and active learning to reduce the cost of labeling samples.However,this method is difficult to effectively improve the model performance because it does not consider the feature representation performance of the examples on the pretext task.In order to overcome this shortcoming,we propose a deep active sampling framework with self-supervised representation learning.
