Artificial intelligence (AI) could soon become more energy-efficient and faster, thanks to a new approach developed at the ...

Traditional experimental methods for evaluating gas adsorption performance of metal–organic frameworks (MOFs) are costly and time-consuming, while ...

Pea-sized brains grown in a lab have for the first time revealed the unique way neurons might misfire due to schizophrenia and bipolar disorder, psychiatric ailments that affect millions of people ...

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...

In a court filing, the tax agency said a decades-old ban on campaigning by tax-exempt groups should not apply to houses of worship speaking to their own members. By David A. Fahrenthold David A.

Abstract: We propose and demonstrate a multi-radar interference mitigation technique in a photonic radar utilizing a nonlinear deep neural network (N-DNN). Trained with interference signals of varying ...

Despite the widespread success of neural networks, their susceptibility to adversarial examples remains a significant challenge. Adversarial training (AT) has emerged as an effective approach to ...

1 School of Computer Science, Technological University Dublin, Dublin, Ireland 2 ADAPT Research Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland Previous work ...