G PU companies, like AMD and Nvidia, spend huge sums of money every year on researching rendering techniques, either to ...

Examples like Intel's Loihi chips tend to get competitive performance out of far lower clock speeds and energy use, but they ...

Artificial neural networks have been applied to problems ... unit and its function is illustrated in Figure 1a. It receives input from a number of other units or external sources, weighs each ...

When visual information enters the brain, it travels through two pathways that process different aspects of the input. For ...

Neural networks are one typical structure on which artificial intelligence can be based. The term "neural" describes their ...

Infomorphic neurons, developed by researchers, are designed to learn independently and self-organize within artificial neural networks. Inspired by biological neurons, they process input signals in ...

Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light—a breakthrough ...

An artificial neural network typically consists of several layers composed of individual neurons. An input signal passes through these layers and is processed by artificial neurons in order to ...

“By making AI more interpretable and robust, our work will help ensure that deep learning technology is not only powerful but ...

Press Release Helm.ai, a leading provider of advanced AI software for high-end ADAS, autonomous driving, and robotics automation, today introduced Helm.ai Driver, a real-time deep neural network (DNN) ...

This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...