1 citations · 1 across the 4 of their papers we have counts for
5 papers
Morphology classification for galaxies in the Kilo Degree Survey using a label-efficient self-supervised learning framework
Xu Huang, Rui Li, Liang Gao +14
Galaxy morphology classification is fundamental to understanding galaxy formation and evolution. The advent of large-scale sky surveys has produced an unprecedented volume of galax…
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…
Identifying Compton-thick AGNs with Machine learning algorithm in Chandra Deep Field-South
Rui Zhang, Xiaotong Guo, Qiusheng Gu +7
Compton-thick active galactic nuclei (CT-AGNs), which are defined by column density , emit feeble X-ray radiation, eve…
Optical+NIR analysis of a Newly Confirmed Einstein ring at z1 from the Kilo-Degree Survey: Dark matter fraction, total and dark matter density slope and IMF
Rui Li, Nicola R. Napolitano, Giuseppe D Ago +16
We report the spectroscopic confirmation of a bright blue Einstein ring in the Kilo Degree Survey (KiDS) footprint: the Einstein ``blue eye''. Spectroscopic data from X-Shooter at…
Multi-Layer Perceptron for Predicting Galaxy Parameters (MLP-GaP): stellar masses and star formation rates
Xiaotong Guo, Guanwen Fang, Haicheng Feng +1
The large-scale imaging survey will produce massive photometric data in multi-bands for billions of galaxies. Defining strategies to quickly and efficiently extract useful physical…