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Compressed sensing is far more mathematically rigorous.


I don't think we know what's in the black box here. It could be an equivalent relatively unopinionated regularizer ("the pixel domain will be locally smooth, to the extent it has edges they're spatially contiguous") or it could be "just look up the most similar image from a library and present that instead" or anywhere in between. :)


They specifically said they use deep learning which implies a sizeable neural network.


But they're using it to eliminate stray or environmental EMI from the RF signals. That might not create fake stuff at the voxel level. Depends on the specifics.




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