Itcanidentifydifferentcomponentsthroughvisualidentifyingsystem, and mount microminiaturizeflat chip with high speed and high precision, and also including subtleICandabnormity components.
Although the artificial neural networks used in the research are much less complex than the human visualsystem, this simplicity helped the researchers to identify and further understand what they believe is a fundamental principle behind why we see illusion: the statistics of our past visual experiences.