Citizen Science hits again with EyeWire

Hear of this crowdsourcing success story at EyeWire:

EyeWire

 

Crowd-sourced science isn’t just fun and games anymore; it has produced a scientific discovery new and important enough to be published in the journal Nature.

The social gaming venture EyeWire lured citizen scientists to follow retinal neurons across multiple two-dimensional photos with the chance to level up and outperform competitors. And with their help, EyeWire has solved a longstanding mystery about how mammals perceive motion.

The use of gamification in conjunction with collaboration techniques, and the multiplication factor of reaching a motivated worldwide crowd,  is giving great results! 


Computers are not very good at identifying objects in an image (to see where one object ends and another one begins), something humans do at a glance.  On this particular game, EyeWire, there are more than 120.000 players from 100 countries coloring the presented neuron cells.  Players are doing the job of identifying cell by cell the path from the eye to the brain.

But that’s not the only thing the crowd is contributing with, because the players’ results is also used to train ‘learning algorithms’ in identifying objects in an image.  Learning algorithms are a very special kind of programs that can adapt through feedback. So when we give to the algorithm a positive (or negative) example of output, the program changes some internal parameters in order to adapt and give the desired outcome. With this game, the images with the colored cells that humans are doing in the game are being used as positive examples.  Next generation of image recognition programs will be more powerful also thanks to crowdsourcing.

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