The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Choosing the right method for multimodal AI—systems that combine text, images, and more—has long been trial and error. Emory ...

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Across the U.S., hundreds of sites on land or in lakes and rivers are heavily contaminated with hazardous waste produced by ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

In the rapidly evolving realm of genetics, the integration of artificial intelligence (AI) has ushered in new perspectives on therapeutic approaches and evolutionary processes. Traditional genetic ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...