I’m training a CNN for plant diseases recognition and the training set is composed by laboratory images. I am achieving low precision in my validation and test sets as they are composed of images taken in the field and which contain an extremely varied dynamic range. Is there a way to introduce data augmentation on my training set based on the validation set in order to get a better acurracy?