I have seen tutorials online saying that you should do data augmentation AFTER doing the train/val/test split. However, when I go online to read some research papers, I see numerous instances of authors saying that they first do data augmentation on the dataset and then split it because they don't have enough data. Is it just that these are silly mistakes, even for papers with many citations, or is this acceptable?
Example: Research paper. they say: "Among these selected 480 images, 94 images were col-lected while changing the viewing angle, including images of 30 youngapples, 32 expanding apples, and 32 ripe apples.These 480 images were then expanded to 4800 images using dataaugmentation methods, yielding the training dataset. The training da-taset is used to train the detection model. The remaining 480 images areused as the test dataset to verify the detection performance of theYOLOV3-dense model".