Astronomy

Neural networks are making it possible to view parts of the Moon that are perpetually shrouded by darkness. Researchers devised a method called Hyper-effective Noise Removal U-net Software (HORUS) to remove noise from images of the Moon’s south pole.

The United States space agency is upgrading the system that pilots its helicopter on the Red Planet. The National Aeronautics and Space Administration (NASA) announced that Ingenuity, a drone sent to Mars as part of its 2020 mission to Mars, will receive a new collision-avoidance algorithm.

Astronomers may use deep learning to keep the sun in focus.What’s new: Researchers at the U.S. National Aeronautics and Space Administration (NASA), Catholic University of America, University of Oslo, and elsewhere developed a model that helps recalibrate a space telescope focused on the sun.

A machine learning model is scouring the cosmos for undiscovered planets. Astronomers from the University of Warwick developed a system that learned to identify faraway worlds in a dataset of thousands of candidates.

Are your scientist friends intimidated by machine learning? They might be inspired by a primer from one of the world’s premier tech titans. Former Google CEO Eric Schmidt and Cornell PhD candidate Maithra Raghu school scientists in machine learning in a sprawling overview.

The origin of the brief, high-intensity signals from outer space called fast radio bursts baffles astronomers. Now AI is generating real-time data to help solve the mystery.