Artificial neural networks are inspired by the early models of sensory processing by the brain. An artificial neural network can be created by simulating a network of model neurons in a computer ...

When designing a robot, such as Boston Dynamics' anthropomorphic robot Atlas, which appears exercising and sorting boxes, ...

In this work, residual fatigue life prediction models have been created through neural networks for the purpose of performing probabilistic life predictions of damaged structures in real-time and ...

The brain's ability to track orientation and position is essential for memory, navigation, and decision-making. Traditionally ...

The goal of the Journal is as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that ...

AI applications like ChatGPT are based on artificial neural networks that, in many respects, imitate the nerve cells in our ...

This article establishes a neural network-based technique for automatic peak picking in 2D NMR spectroscopy, demonstrating a ...

Neural implants contain integrated circuits (ICs) — commonly called chips — built on silicon. These implants need to be small and flexible to mimic circumstances inside the human body. However, the ...

A study by the University of Bonn demonstrates a novel training method for spiking neural networks, which are ...

Western University researchers have developed a novel technique using math to understand exactly how neural networks make decisions.

Researchers have explored the potential of deep neural networks (DNNs) in transforming fragrance design. By analyzing the sensing data of 180 essential oils, the DNN was trained using the odor ...

A team of researchers has unveiled a groundbreaking method leveraging Graph Neural Networks (GNNs) and transfer entropy to significantly enhance the prediction of mesozooplankton community dynamics ...