1 citations · 4 across the 10 of their papers we have counts for
4 papers · 1 filter
Reducing False Positives in Strong-Lens Searches with Generalized-Mean Consensus of Machine-Learning Ensembles in the Kilo-Degree Survey
Ziqi Li, Rui Li, Xu Huang +11
Context. In wide-field surveys, the main challenge is not just classifier sensitivity, but the overwhelming number of false positives. Searching for strong lenses among millions to…
LenNet: Direct Detection and Localization of Strong Gravitational Lenses in Wide-Field Sky Survey Images
Pufan Liu, Hui Li, Ziqi Li +9
Strong gravitational lenses are invaluable tools for addressing fundamental questions in astrophysics, from the nature of dark matter to the expansion of the universe. While curren…
Identification of gravitational lenses obscured by foreground light in the KiDS dataset using U-Nets and ResNets
S. Liu, Rui Li, J. Jia +13
*Context.* Many lensing images are often obscured by foreground light from the central galaxies, making them challenging to detect. *Aims.* To address the limitations of previous l…
MIU2Net: weak-lensing mass inversion using deep learning with nested U-structures
Han W. G., An Zhao, Xinyue Chen +5
One of the primary goals of next-generation gravitational lensing surveys is to measure the large-scale distribution of dark matter, which requires accurate mass inversion to conve…