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by mat_kelcey 2953 days ago
no, it won't directly. conv nets handle translation invariance but not scale invariance. having said that there's no reason you can't use aggressive data augmentation for this (resizing before patch sampling). i wonder how much the semi supervised approach might help too; if you've labelled _only_ small bees in a subset of the data, trained a model, applied to a larger dataset & retrained there will be a small amount of detections (that are true positives) to bees that are slightly larger (and smaller) than the ones you labelled.... (maybe?)
2 comments

Ok. Why isn't there a kind of network function that works with scaling, like convolution works with translation?
I think a CNN can handle scale invariance e.g. With max pooling