Answer
Image augmentation techniques create new training examples by applying small changes to existing images, such as rotating, flipping, or adjusting brightness.
Real-world example A team training a plant disease detector uses image augmentation to rotate and flip leaf photos, helping the model recognize diseased leaves from any angle.