ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

Another day, another malware attack on smartphones. Researchers at Unit 42, the threat intelligence arm of Palo Alto Networks, have revealed a sophisticated spyware known as “Landfall” targeting ...

As the economy and society continue to develop, the range of underwater vehicles is expanding and technology is constantly being upgraded. Consequently, it is becoming increasingly difficult to ...

The First Affiliated Hospital of Dalian Medical University, Dalian, China With the continuous updates and iterations of diagnostic equipment and technologies, the diagnosis of lung diseases has ...

Abstract: A feedforward optical neural network for image recognition is demonstrated through free-space optics in which the nonlinear activation function is provided by a resonant semiconductor ...

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...

Abstract: The graph neural network (GNN) exhibits noteworthy performance in hyperspectral image classification (HSIC) due to its efficient message-passing structure, which employs the multilayer ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

Although there have been significant advances in the field of image restoration recently, the system complexity of the state-of-the-art (SOTA) methods is increasing as well, which may hinder the ...