IEEE Consumer Electronics Magazine · 2020 · 13 citations · 21 references
ComputingComputer ScienceData ManagementData MiningMachine LearningDeep LearningGenerative ModelingOptimization For Machine LearningOverfittingRepresentation LearningSupervised LearningData AugmentationDeep Learning For IotFeature AugmentationNeural Network ModelingParallel Deep LearningTraining
Learnable data augmentation is a technique where a neural network learns to create modified data samples that improve the training outcome from a second, parallel neural network. This is a relatively new approach to dataset augmentation that has inspired many variations in the last few years. In this article the most signficiant of these advanced data augmentation strategies are summarised and discussed.
21
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang, Moustapha Cissé, Yann Dauphin et al. · arXiv (Cornell University) · 2017 · 4.8K citations · Full text
AutoAugment: Learning Augmentation Strategies From Data
Ekin D. Cubuk, Barret Zoph, Dandelion Mané et al. · 2019 · 2.7K citations