It is an open issue to train effective deep network models on class imbalance datasets. In the widely used cost‐sensitive imbalanced learning methods, the costs are based on the losses or class probabilities of samples. In this paper, it is discovered that these traditional cost‐sensitive methods discard the clustering feature, and introduce the er...

Focal learning on stranger for imbalanced image segmentation

10.1049/ipr2.12410