Data Augmentation
The cheapest way to get more training data isn't collecting more — it's transforming the data you already have in ways that shouldn't change the label. A flipped photo of a cat is still a cat; a rotated photo of a stop sign is still a stop sign (probably). What you choose to augment with is a direct statement of what invariances you want the model to learn.