About Augment Images for Training

We know that new augmentation methods are applied randomly at all times.

Insufficient learning, the result is slightly different even though it's the same epoch due to the same data. Can you tell me if this is due to insufficient learning?

Answer 1

[Mahesh Taparia]

Hi,

You can try with all possible data augmentation techniques like flip, rotation, cropping, scaling, adding noise, translation etc. If it won’t work, there may be the chance that your dataset became invariant even after doing data augmentation due to enough data.