总体而言，《IEEE Transactions on Neural Networks and Learning ...

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

Neuronal network dynamics and electrophysiology encompass the study of how networks of neurons communicate, adapt and process information through electrical signals. This field integrates insights ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

A new publication from Opto-Electronic Technology; DOI   10.29026/oet.2025.250011, discusses integrated photonic synapses, neurons, memristors, and neural networks for photonic neuromorphic computing.

Uncovering the relationship between structure (connectivity) and function (neuronal activity) is a fundamental question across many areas of biology. However, investigating this directly in animal ...

Neural circuits in the brain are highly sophisticated biological systems, orchestrating ultra-fast, parallel computations ...

Researchers have mapped and catalogued more than 70,000 synaptic connections from about 2,000 rat neurons, using a silicon chip capable of recording small yet telltale synaptic signals from a large ...

In order to uncover the relationship between structure and function, researchers used microfluidic devices to study neuronal networks. Uncovering the relationship between structure (connectivity) and ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...