What data augmentation techniques are commonly used in computer vision, and how do you ensure augmentations are appropriate for your specific task?

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Data augmentation artificially expands training datasets by applying transformations that preserve semantic content while varying appearance. This improves model generalization by exposing it to diverse variations during training, reducing overfitting when data is limited.