I’m working on a CNN project and I’m trying to improve it. I was told me how I augment my data can greatly influence my results. I was told to look into inception style data augmentation, but I can’t find anything on. Does anyone know what that is and where I can find out about it, as well as in any other augmentation techniques/styles?
This is what I have so far:

train_transform = transforms.Compose([
transforms.Resize(224),
transforms.CenterCrop(224),
transforms.RandomRotation(10),      # rotate +/- 10 degrees
transforms.RandomHorizontalFlip(),  # reverse 50% of images
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406],
[0.229, 0.224, 0.225])
])
test_transform = transforms.Compose([
transforms.Resize(224),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406],
[0.229, 0.224, 0.225])
])

I am using the torchvison transform page on PyTorch, but are there any other augmentation styles or techniques anyone can point me to?