No, unless you've explicitly trained it to match photos to cartoon images. The article is a bit sensationalistic when it says 'what if a NN would misclassify a pedestrian crossing as an empty road?'. The truth is you can't compare a simple photo recognizer with human perception. Human perception obviously can do far more advanced things than just matching photos to memories of photos, it's not even very good at matching photos. We have depth perception, we have object isolation, we can remember and abstract shapes, we can extrapolate and interpolate, we have loads and loads of context. We don't see the world in RGBA. We see the world as a continuous stream of related information.

All these systems together make sure a human would never[1] mistake a pedestrian crossing to an empty road, and allow us to match abstract paintings to realistic images. Any serious artificial autonomous agent would similarily consist of many independent but contextualized systems.

edit: 1] Never as in, never unless the pedestrian makes a good effort to look like an empty road to all of those systems

I took Yann LeCun's machine learning class at NYU. He demo'ed a system that learned how to recognize human faces from photographs. When he pointed it at a comic book (system was only trained on photos, not drawings), it also recognized the faces in it.

I would say that the NN learns to recognize what the training photos of this person have in common, so if the drawing is similar in the respects that you have trained for, it might be recognized.