Neural network optimisation has emerged as a transformative approach in microwave engineering, driving enhancements in both the accuracy and speed of electromagnetic (EM) simulations and circuit ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

A Queen’s research team has developed a new way to train AI systems so they focus on the bigger picture instead of specific, ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution of neural network models. According ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

An EEG (electroencephalogram) is a painless test that uses small sensors placed on the scalp to measure the brain's electrical activity.