What is test-time augmentation (TTA) in vision inference?

TTA improves predictions by applying augmentations during inference and aggregating outputs.

Test-Time Augmentation applies transformations like flipping, scaling, and cropping during inference. The model predicts on each transformed version, and results are aggregated (averaging or voting). This reduces variance and improves robustness without retraining.