3 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
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…
cs.CV2022
Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization
Mengyin Liu, Chao Zhu, Hongyu Gao +4
With the prosperity of e-commerce industry, various modalities, e.g., vision and language, are utilized to describe product items. It is an enormous challenge to understand such di…