Comparing Different Automatic Image Augmentation Methods in PyTorch
Read OriginalThis article provides a detailed comparison of four automatic image augmentation techniques available in PyTorch: AutoAugment, RandAugment, AugMix, and TrivialAugment. It explains how these methods help reduce overfitting by generating variations of training data and includes performance benchmarks using a ResNet-18 model on a simple dataset, with executable code provided on GitHub.
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