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FMix: Enhancing Mixed Sample Data Augmentation
We propose FMix, an MSDA that uses binary masks obtained by applying a threshold to low frequency images sampled from Fourier space, obtaining new state-of-the-art results on CIFAR-10 and Fashion-MNIST. Expand
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The Effect of Physics-Based Corrections and Data Augmentation on Transfer Learning for Segmentation of Benthic Imagery
Ocean observation has been greatly improved by the use of Autonomous Underwater Vehicles and Remotely Operated Vehicles, and the high quality and high quantity of imagery they produce. This quantityExpand
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