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20222026
most citedAutomatic detection of low surface brightness galaxies from SDSS images

24 citations · 61 across the 14 of their papers we have counts for

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Showing astro-ph.SRShow all

8 papers · 1 filter

astro-ph.SR2026

MSFA-Net: An Advanced Deep Learning Model for Identifying Blue Horizontal-Branch Stars from LAMOST DR12

Mingyuan Wang, Xiaoming Kong, Jie Ju +2

Blue horizontal-branch (BHB) stars are low-mass, core helium-burning objects with nearly constant luminosities, making them powerful tracers of old, metal-poor populations and valu…

astro-ph.SR2026

A Generalist Model Including Evolved Star Mass and Age

Mengmeng Zhang, Yude Bu, Siqi Wang +10

Determining precise stellar ages and masses for evolved giants is crucial for Galactic archaeology but challenged by spectral degeneracies. Gaia's low-resolution XP spectra offer a…

astro-ph.SR2024

An adaptive parameter estimator for poor-quality spectral data of white dwarfs

Duo Xie, Jiangchuan Zhang, Yude Bu +3

White dwarfs represent the end stage for 97% of stars, making precise parameter measurement crucial for understanding stellar evolution. Traditional estimation methods involve fitt…

astro-ph.SR2024

SPT: Spectral Transformer for Red Giant Stars Age and Mass Estimation

Mengmeng Zhang, Fan Wu, Yude Bu +4

The age and mass of red giants are essential for understanding the structure and evolution of the Milky Way. Traditional isochrone methods for these estimations are inherently limi…

astro-ph.SR2023

Estimating Stellar Parameters and Identifying Very Metal-poor Stars Using Convolutional Neural Networks for Low-resolution Spectra (R~200)

Tianmin Wu, Yude Bu, Jianhang Xie +5

Very metal-poor (VMP, [Fe/H]<-2.0) stars offer a wealth of information on the nature and evolution of elemental production in the early galaxy and universe. The upcoming China Spac…

astro-ph.SR2022

Se-ResNet+SVM model: an effective method of searching for hot subdwarfs from LAMOST

Cheng Zhongding, Kong xiaoming, Wu Tianmin +5

In this paper, we apply the feature-integration idea to fuse the abstract features extracted by Se-ResNet with experience features into hybrid features and input the hybrid feature…

astro-ph.SR2022

Identifying hot subdwarf stars from photometric data using Gaussian mixture model and graph neural network

Wei Liu, Yude Bu, Xiaoming Kong +2

Hot subdwarf stars are very important for understanding stellar evolution, stellar astrophysics, and binary star systems. Identifying more such stars can help us better understand…

astro-ph.SR2022★ 4 cited

Searching for Barium Stars from the LAMOST Spectra Using the Machine Learning Method: I

Fengyue Guo, Zhongding Cheng, Xiaoming Kong +5

Barium stars are chemically peculiar stars that exhibit enhancement of s-process elements. Chemical abundance analysis of barium stars can provide crucial clues for the study of th…