Extra 'eye' movements are the key to better self-driving cars

Andrea Benucci and colleagues at the RIKEN Center for Brain Science has developed a way to create artificial neural networks that learn to recognize objects faster and more accurately. The study, recently published in the scientific journal PLOS Computational Biology, focuses on all the unnoticed eye movements that we make, and shows that they serve a vital purpose in allowing us to stably recognize objects. These findings can be applied to machine vision, for example, making it easier for self-driving cars to learn how to recognize important features on the road.

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