To test their device’s ability to see objects through neuromorphic computing, the researchers used it in facial recognition experiments assisted by machine learning. “The facial recognition experiment was a preliminary test to check our optoelectronic neuromorphic computing,” professor Jayan Thomas said. “Since our device mimics vision-related brain cells, facial recognition is one of the most important tests for our neuromorphic building block.”
They found that their device was able to successfully recognize the portraits of four different people. “Because of the nature of the superstructure, it shows a light-assisted memory effect,” Basudev Pradhan, assistant professor at the Central University of Jharkhand in India, said. “This is similar to humans’ vision-related brain cells. The optoelectronic synapses we developed are highly relevant for brain-inspired, neuromorphic computing.”
The researchers hope that the graphene-PQD superstructures will open new directions in the development of highly efficient optoelectronic devices. Potential applications include drone-assisted rescues and defense. “Such features can also be used for aiding the vision of soldiers on the battlefield,” researcher Sonali Das said. “Further, our device can sense, detect, and reconstruct an image along with extremely low power consumption, which makes it capable for long-term deployment in field applications.”
The team plans to continue its collaboration to refine the device, including using it to develop a circuit-level system.
The research was published in Science Advances (www.doi.org/10.1126/sciadv.aay5225).