In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and ...

University of New South Wales researchers have developed a simplified residual network-based architecture method to filter out noise from electroluminescence images of solar modules.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Researchers in Australia have developed a simplified residual network-based architecture method to filter out noise from electroluminescence images of PV modules. The proposed technique reportedly ...

Machine unlearning helps AI models forget specific data they were trained on, addressing a growing need for privacy, legal ...

Imagine diagnosing cancer not with a supercomputer but on an ordinary laptop instead. Sounds like science fiction? Thanks to ...

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the ...

A deep learning (DL)–based model achieved a high accuracy in pancreas segmentation for patients with chronic pancreatitis (CP) and healthy individuals, a new study finds. The model showed robust ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

San Diego (UCSD), is a leader in a field known as “physics-guided deep learning,” having spent years incorporating our knowledge of physics into artificial neural networks. The work has not only ...

Abstract: Accurate schematic detection in Power Distribution Networks ... methods often struggle with the complexity and scale of modern PDNs, while standalone deep learning approaches face challenges ...