You're thinking simple image augmentations. These nets learn much more complex invariants. Basically to isolate concepts from irrelevant context. The point is y

You're thinking simple image augmentations. These nets learn much more complex invariants. Basically to isolate concepts from irrelevant context. The point is you can't remove that image from the training data (not practically) and the experiment is pointless if it's in there.