1 citations · 1 across the 6 of their papers we have counts for
6 papers
An Ultra-Fast Image Simulation Technique with Spatially Variable Point Spread Functions
Zeyu Bai, Peng Jia, Jiameng Lv +3
Simulated images are essential in algorithm development and instrument testing for optical telescopes. During real observations, images obtained by optical telescopes are affected…
A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Mingxiang Fu, Yu Song, Jiameng Lv +14
The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount…
An Image Quality Evaluation and Masking Algorithm Based On Pre-trained Deep Neural Networks
Peng Jia, Yu Song, Jiameng Lv +1
With the growing amount of astronomical data, there is an increasing need for automated data processing pipelines, which can extract scientific information from observation data wi…
CSST Strong Lensing Preparation: a Framework for Detecting Strong Lenses in the Multi-color Imaging Survey by the China Survey Space Telescope (CSST)
Xu Li, Ruiqi Sun, Jiameng Lv +29
Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing…
Perception of Misalignment States for Sky Survey Telescopes with the Digital Twin and the Deep Neural Networks
Miao Zhang, Peng Jia, Zhengyang Li +3
Sky survey telescopes play a critical role in modern astronomy, but misalignment of their optical elements can introduce significant variations in point spread functions, leading t…
Image Restoration with Point Spread Function Regularization and Active Learning
Peng Jia, Jiameng Lv, Runyu Ning +5
Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae. Analysing and processing these images can reveal intricate intern…