Invariance encoding in sliced-Wasserstein space for image classification with limited training data
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Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform when training data are limited and thus require data augmentation strategies that r... ...
