4 ms·

Can't wait to read about Inception V4 being trained on adversarial.io for better noise resistance :)

• _the_inflator 6y ago
  Yes, the irony: this app makes image recognition even more effective.
  • Imnimo 6y ago
    I don't really think this is true for two reasons. First, the app doesn't add anything that someone training a classifier couldn't just do themselves. If I want to train my network against adversarial inputs, I can just generate them myself at training time on my own training data - it's not particularly helpful for me to have a bunch adversarially-perturbed but unlabeled images. Second, and more importantly, it's not sufficient to just train on adversarial examples taken from another network. You might learn to be robust against the specific weaknesses of that other network, but your new network will have its own idiosyncratic weaknesses. To be effective, adversarial training (https://arxiv.org/pdf/1706.06083.pdf https://arxiv.org/pdf/1706.06083.pdf) needs an adversary that adapts to the network as it trains. In other words, you need your adversary to approximate your current weaknesses at each step of training.