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 ...

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

Earth Scientists have used machine learning for at least three decades and the applications span is large, from remote sensing to analysis of well log data, among many others. Although machine ...

It’s been ten years since AlexNet, a deep learning convolutional neural network (CNN) model running on GPUs, displaced more traditional vision processing algorithms to win the ImageNet Large Scale ...

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

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

Recent advances in neural network methodologies have significantly reshaped the fields of electrical tomography and moisture analysis. By integrating artificial neural networks (ANNs) for both image ...

Future Market Insights (FMI) projects the Neural Processors Market to grow from USD 176 million in 2025 to USD 1,010 million by 2035, advancing at a 19.1% CAGR. This surge is being driven by the ...

Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the ...

The UK Supreme Court has ruled that an artificial neural network (ANN) can be patented, marking a pivotal moment for AI innovations. This decision, favoring Emotional Perception AI, clarifies that a ...

This technical paper titled “Can one hear the shape of a neural network?: Snooping the GPU via Magnetic Side Channel” was presented by researchers at Columbia University, Adobe Research and University ...