3 ms·
Curious what you're referring to? My knowledge of this area is not that broad or deep at all.
by civilized 5y ago
Curious what you're referring to? My knowledge of this area is not that broad or deep at all.
- a-dub 5y agomel warped cepstra still see use and improve performance for nns, is one example.
- MauranKilom 5y agoThe weight patterns that convolutional neural networks develop are pretty familiar in many ways. For example, the first layer will generally end up with small-scale feature detectors, such as borders, gradients/color pairs and certain textures, at various scales and angles. Try an image search for "imagenet first layer" to see examples. I took the comment to mean "we have ourselves discovered certain filters being useful (e.g. https://en.wikipedia.org/wiki/Gabor_filter https://en.wikipedia.org/wiki/Gabor_filter), and the networks now also discover this same information".
- a-dub 5y agoit is true that the promise of dl succeeds at finding some handcrafted features. it is also true that (at least the last time i checked), the state of the art is still making use of handcoded transforms that are derived from results in psychophysics.