New research offers clues to what goes on inside the minds of machines as they learn to see. Instead of attempting to account for a neural network’s decision-making on a post hoc basis, their method shows how the network learns along the way, by revealing how much the network calls to mind different concepts to help decipher what it sees as the image travels through successive layers.
Accurate neural network computer vision without the ‘black box’
