Machine learning algorithms train on data to find the best set of weights for each independent variable that affects the predicted value or class. The algorithms themselves have variables, called ...

Beyond achieving technical excellence, the study underscores the practical utility of explainable AI in flood risk management ...

Mathematicians have developed a new approach to machine learning aimed at experimental imaging data. Rather than relying on the tens or hundreds of thousands of images used by typical machine ...

PhoSim simulates the atmosphere, including air turbulence, as well as distortions from the shape of the telescope’s mirrors and the electrical properties of the sensors. The photons are propagated ...

Each satellite image studied by the algorithm was composed of a ten-by-ten-meter square, and each square may contain various land covers ranging from grass, road, building roofs, vehicles and ponds.

A new machine-learning technique has significantly reduced noise in images taken by scanning transmission electron microscopy (STEM). Developed by researchers in Ireland, the algorithm could make it ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right). Credit: Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00912-9 ...