Fruit flies are able to consistently tell apart among individuals based on sight alone. Researchers have now built a neural network that mimics the fruit fly's visual system and can distinguish and re-identify flies.
In an interdisciplinary project funded by a Canadian Institute for Advanced Research (CIFAR) Catalyst grant, researchers at the University of Guelph and the University of Toronto, Mississauga combined expertise in fruit fly biology with machine learning to build a biologically-based algorithm that churns through low-resolution videos of fruit flies in order to test whether it is physically possible for a system with such constraints to accomplish such a difficult task.
Fruit flies have small compound eyes that take in a limited amount of visual information, an estimated 29 units squared. The traditional view has been that once the image is processed by a fruit fly, it is only able to distinguish very broad features.
The computer program has the same theoretical input and processing ability as a fruit fly and was trained on video of a fly over two days. It was then able to reliably identify the same fly on the third day with high score