University of Illinois professor Klara Nahrstedt received $275,000 from the National Science Foundation to develop streaming ...

In 2025 Artprice successfully integrated all the key tools of its proprietary AI (Intuitive Artmarket®) into its internal database ...

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

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the ...

Abstract: In this work, a novel neural network architecture called MalaNet is proposed for the detection and diagnosis of malaria, an infectious disease that poses a major global health challenge. The ...

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

Abstract: Neural networks have become increasingly effective at many difficult machine learning tasks. However, the nonlinear and large-scale nature of neural networks makes them hard to analyze, and, ...

Introduction: In the field of brain-computer interfaces (BCI), motor imagery (MI) classification is a critically important task, with the primary objective of decoding an individual's MI intentions ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

The applications of neural network models, shallow or deep, to information retrieval (IR) tasks falls under the purview of neural IR. Over the years, machine learning methods-including neural networks ...