The deep neural network models that power today's most demanding machine-learning applications are pushing the limits of traditional electronic computing hardware, according to scientists working on a ...

Researchers have developed a deep-learning-based surrogate model that dramatically speeds up simulations of nonlinear optical ...

Researchers have published a programmable framework that overcomes a key computational bottleneck of optics-based artificial intelligence systems. In a series of image classification experiments, they ...

Programmable optical particle transport based on structured light plays a crucial role in microscale manipulation. Scientists ...

As part of this week's SPIE Optics & Photonics conference program Emerging Topics in Artificial Intelligence, Asst. Prof. Logan G. Wright, of Yale University, presented an invited paper, entitled ...

Research on ONNs began as early as the 1960s. To clearly illustrate the development history of ONNs, this review presents the evolution of related research work chronologically at the beginning of the ...

This study presents MPALM, a novel microscopy technique that captures nanoscale biomolecular dynamics, overcoming limitations ...

Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our ...

Fiber-optic technology revolutionized the telecommunications industry and may soon do the same for brain research. A group of researchers from Washington University in St. Louis in both the McKelvey ...

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research I have used a phenomenon called “quantum tunnelling” to ...