Comparing deep neural networks against humans: object recognition when the signal gets weaker

Understand

Human visual object recognition is typically rapid and seemingly effortless, as well as largely independent of viewpoint and object orientation.

• Until very recently, animate visual systems were the only ones capable of this remarkable computational feat.
• This has changed with the rise of a class of computer vision algorithms called deep neural networks (DNNs) that achieve human-level classification performance on object recognition tasks.
• Furthermore, a growing number of studies report similarities in the way DNNs and the human visual system process objects, suggesting that current DNNs may be good models of human visual object recognition.