A new AI foundation model transforms neurological diagnostics by using data from electrical brain activity to analyze neural ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, where data ...

A collaborative research team led by Professor Pan Feng from the School of New Materials at Peking University Shenzhen ...

Frontiers Events is a rapidly growing calendar management system dedicated to the scheduling of academic events. This includes announcements and invitations, participant listings and search ...

Therefore, this research introduces a neural network-centered process especially fitted for analyzing aerial vehicles (Mohammed et al., 2025). Detection, tracking, counting, trajectory prediction, and ...

This particular type of neural network is called a Spiking Neural Network (SNN) which uses discrete events, called “spikes”, instead of continuous real-valued activations.

These results highlight the potential of the Autoencoder–GCN pipeline as a scalable and reliable solution for AMS structure recognition under real-world constraints.

Toughness reflects extensibility, which is critical for accommodating electrode volume changes in batteries, primarily due to thermal expansion. However, polymer toughness has received less attention ...