2 papers
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…