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20192025
most citedDiversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation

18 citations · 46 across the 12 of their papers we have counts for

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eess.IV2020★ 4 cited

Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation

Tiexin Qin, Ziyuan Wang, Kelei He +3

Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance…