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They've written though that they have chosen a particular layer in the network, which reads like "independent of the output layer". Features in such a layer co
by rndn 11y ago
They've written though that they have chosen a particular layer in the network, which reads like "independent of the output layer". Features in such a layer correlate with certain classes, but I don't think they have dealt with classes at all. If that's the case, then the question is how they've amplified the detected features.
- murbard2 11y agoYes they play with various layers. Layers closer to the input act more like edge enhancers, while higher layers emphasize whole objects ("animal" enhancers). You get increasingly less syntactical and increasingly more semantic as you go deeper in the network.
- nitrogen 11y agoSo "lower" layers are closer to the input, while "higher" layers are closer to the output?