'Hunting for treasures' with AI: Astronomers detect rare neutral atomic-carbon absorbers with deep neural network
Recently, an international team led by Prof. GE Jian from the Shanghai Astronomical Observatory of the Chinese Academy of Sciences conducted a search for rare weak signals in quasar spectral data released by the Sloan Digital Sky Survey III (SDSS-III) program using deep learning neural networks. By introducing a new method to explore galaxy formation and evolution, the team showcased the potential of artificial intelligence (AI) in identifying rare weak signals in astronomical big data. This study was published ...
















