Imaging system shows potential in autonomous technologies

The technology is said to combine transparent light detectors with advanced neural network and promises to find applications in automated manufacturing, biomedical imaging and autonomous driving. A paper on the system is published in Nature Communications.

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The imaging system exploits the advantages of transparent, nanoscale, highly sensitive graphene photodetectors developed by Zhaohui Zhong, U-M associate professor of electrical and computer engineering, and his group.

"The in-depth combination of graphene nanodevices and machine learning algorithms can lead to fascinating opportunities in both science and technology," said Dehui Zhang, a doctoral student in electrical and computer engineering. "Our system combines computational power efficiency, fast tracking speed, compact hardware and a lower cost compared with several other solutions."

The graphene photodetectors in this work have been adjusted to absorb about 10 per cent of the light they are exposed to. Because graphene is so sensitive to light, this is sufficient to generate images that can be reconstructed through computational imaging. The photodetectors are stacked behind each other, resulting in a compact system, and each layer focuses on a different focal plane, which enables 3D imaging.