Hacker News new | ask | show | jobs
by jswulff 1658 days ago
One thing to note is that here noise != Gaussian iid noise, so these are not typical white noise images. I think we were not really clear on that part, but for us noise is basically a random process, which takes a seed as input (plus potentially some very low-level assumptions over image statistics, such as a 1/f spectrum) and produces a synthetic image.

It is then possible to generate arbitrary amounts of these images as samples from the stochastic process - these images exhibit certain image-like structures (such as oriented edges), but are as a whole still random and extremely varied, which is good and necessary for the representation learning.

In terms of helping, though, it is important to note that we do not achieve state-of-the-art performance yet, and when looking at absolute performance for a task like image classification, using real images is still better. That being said, something that is in the paper but generally seems to get lost is that our representations work very well when analyzing data that is very different from normal images, such as medical images or satellite images.
2 comments
vanderZwan 1658 days ago
But then you aren't really throwing "random noise" at it are you? It's more like you are throwing generated data sets with abstract structures at it, and use the randomization part to ensure that it does not overfit on other accidental structures that might be in an individual image, because the randomization ensures that there are no other structures to speak of in the "average" (which does sound like a very sensible way to train a network on abstract structures). Or do I misunderstand the method here?
link
l33tman 1658 days ago
I'm pretty sure the title is clickbait, it's not uncorrelated random per-pixel noise as it gives the impression of.
link
vanderZwan 1658 days ago
Oh for sure, and I don't mean to accuse the authors; if pop-sci articles spread confusion about their work that's not their fault. I just want to clear things up for myself
link
a_e_k 1658 days ago
It could be very interesting to try Gabor noise.
link
locuscoeruleus 1658 days ago
Why would that be interesting?
link