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

AI models now help fisheries securely analyze vast underwater images in-house. Trained on thousands of seafloor pictures, ...

AWS is making automated reasoning checks, a feature on Bedrock, generally available to customers to start proving truth in their AI systems.

Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform” was published by researchers at TU Dresden, ...

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

In this article, a framework for the analog implementation of a deep convolutional neural network (CNN) is introduced and used to derive a new circuit architecture which is composed of an improved ...

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 ...

The cost of an accurate medical diagnosis is extremely high, particularly in developing nations. Pneumonia is a prevalent ailment that poses a considerable barrier to medical diagnosis because of the ...

A new study shows that astrocytes use a protein called Gat3 to manage ambient GABA levels, helping neurons work together to encode visual input.

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.

Purpose: To evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting ...