Cornell researchers develop optical neural networks for image processing.

Researchers at Cornell University have developed an optical neural network (ONN) that can filter relevant information from a scene before the visual image is detected by a camera, making it possible to build faster, smaller and more energy-efficient image sensors. The ONN pre-processors can achieve compression ratios of up to 800-to-1 while still enabling high accuracy across several representative computer-vision tasks. The researchers believe their work could have practical applications in fields such as early cancer detection research, where cancer cells need to be isolated from millions or billions of other cells.