Few-shot imbalanced classification based on data augmentation
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DOI: 10.1007/s00530-021-00827-0
Abstract: Few-shot imbalanced classification tasks are commonly faced in the real-world applications due to the unbalanced data distribution and few samples of rare classes. As known, the traditional machine learning algorithms perform poorly on the imbalanced… read more here.
Keywords: shot; shot imbalanced; imbalanced classification; data augmentation ... See more keywords