Researchers at Empa have developed machine learning algorithms that reduce preliminary testing in laser-based metal additive manufacturing by about two-thirds without compromising quality. Using ...

A project at Rice University has developed a new machine learning (ML) algorithm intended to improve the identification of biomarkers in optical spectra. As reported in ACS Nano, the algorithm could ...

Professor Iksung Kang, KAIST >Observing the depths of a living brain with clarity has traditionally required expensive, high-end equipment. However ...

A team of international scientists from Lawrence Livermore National Laboratory (LLNL), Fraunhofer Institute for Laser Technology (ILT), and the Extreme Light Infrastructure (ELI) have collaborated on ...

Why standard, cuff-based blood-pressure measurements are insufficient for some desired types of assessments. How electro-optical techniques can be used for consistent, real-time data. The results ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

Laser-based metal manufacturing, including powder bed fusion (PBF) 3D printing, requires precise parameter settings that can change even between batches of identical material. Empa researchers Giulio ...

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...