3 papers
astro-ph.IM2025
Application of Physics-Informed Neural Networks in Removing Telescope Beam Effects
Shulei Ni, Yisheng Qiu, Yunchuan Chen +5
This study introduces {\tt{PI-AstroDeconv}}, a physics-informed semi-supervised learning method specifically designed for removing beam effects in astronomical telescope observatio…
astro-ph.GA2025
Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Yisheng Qiu, Tianwei Zhang, Thomas Möller +4
Interstellar molecules, which play an important role in astrochemistry, are identified using observed spectral lines. Despite the advent of spectral analysis tools in the past deca…
cs.CV2024
Automated Identification and Segmentation of Hi Sources in CRAFTS Using Deep Learning Method
Zihao Song, Huaxi Chen, Donghui Quan +5
Identifying neutral hydrogen (\hi) galaxies from observational data is a significant challenge in \hi\ galaxy surveys. With the advancement of observational technology, especially…