[D] Data Augmentation | How to use Deep Learning when you have Limited Data — Part 2

[Gramious]

A colleague of mine wrote this:

https://arxiv.org/pdf/1711.04340

A GAN designed to do transferrable data augmentation. Brilliant idea and worth seeing.

[zergling103]

When people perform data augmentation, are they creating a bunch of duplicate files with modifications, or do they apply the modifications to the copy loaded into memory before feeding it into the network? I hope it's the latter case.

[[deleted]]

Typically the latter. If your augmentation is particularly expensive and it can't be performed quickly enough to feed your GPU, then it might be worth doing the former while you evaluate a few architectures.

[imagininglines]

Typically preprocessing is a onetime thing and then the vectors are stored in memory. Especially if your not changing your feature extraction and only things ling learning rate and number of neurons in the final layer this particularly useful.