33.1k citations · 35.3k across the 95 of their papers we have counts for
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cs.CV2022★ 6 cited
Understanding CNN Fragility When Learning With Imbalanced Data
Damien Dablain, Kristen N. Jacobson, Colin Bellinger +2
Convolutional neural networks (CNNs) have achieved impressive results on imbalanced image data, but they still have difficulty generalizing to minority classes and their decisions…
cs.CV2021★ 4 cited
DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data
Damien Dablain, Bartosz Krawczyk, Nitesh V. Chawla
Despite over two decades of progress, imbalanced data is still considered a significant challenge for contemporary machine learning models. Modern advances in deep learning have ma…