Grad-CAM after two separate training runs. Both figures show saliency maps derived from fully trained ConvNets on the artificial dataset. In both cases, the models achieve near perfect classification scores, however, the central artifact is asymmetrically covered by the network’s attention, and residual unimportant features such as the line cores still show nonzero contributions.