High-Low Frequency Detectors
Some of the neurons in vision models are features that we aren’t particularly surprised to find. Curve detectors, for example, are a pretty natural feature for a vision system to have. In fact, they had already been discovered in the animal visual cortex. It’s easy to imagine how curve detectors are built up from earlier edge detectors, and it’s easy to guess why curve detection might be useful to the rest of the neural network. High-low frequency detectors, on the other hand, seem more surprising. They are not a feature that we would have expected a priori to find. Yet, when systematically characterizing the early layers of InceptionV1, we found a full fifteen neurons of mixed3a that appear to detect a high frequency pattern on one side, and a low frequency pattern on the other. By “high frequency” and “low frequency” here, we mean spatial frequency — just like when we take the Fourier transform of an image. One worry we might have about the circuits approach to studying neural networks is that we might only be able to understand a limited set of highly-intuitive features. High-low frequency detectors demonstrate that it’s possible to understand at least somewhat unintuitive features.
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