August 20, 2018—Researchers at Stanford University have devised a new type of artificially intelligent camera system that can classify images faster and more energy efficiently, and that could one day be built small enough to be embedded in the devices themselves—something that is not possible today, reported Stanford News.
The work was published in the August 17 Nature Scientific Reports.
“That autonomous car you just passed has a relatively huge, relatively slow, energy intensive computer in its trunk,” said Gordon Wetzstein, an assistant professor of electrical engineering at Stanford, who led the research. Future applications will need something much faster and smaller to process the stream of images, he said.
Wetzstein and Julie Chang, a graduate student and first author on the paper, took a step toward that technology by marrying two types of computers into one, creating a hybrid optical-electrical computer designed specifically for image analysis, according to the report.
According to Stanford News, the first layer of the prototype camera is a type of optical computer, which does not require the power-intensive mathematics of digital computing. The second layer is a traditional digital electronic computer.
While their current prototype, arranged on a lab bench, would hardly be classified as small, the researchers said their system can one day be miniaturized to fit in a handheld video camera or an aerial drone. In both simulations and real-world experiments, the team used the system to successfully identify airplanes, automobiles, cats, dogs and more within natural image settings.
