2026-10-12T04:28:16Z https://www.scidb.cn/oai

10.57760/sciencedb.32005 2026-04-02T11:07:25Z

2026-04-02 LAMOST 光谱数据上数据驱动与混合方法的代表性工作 doi:10.57760/sciencedb.32005 en To provide a more intuitive overview of representative data-driven and hybrid methods developed for LAMOST low-resolution spectra in recent years, several relevant studies are summarized in this table. Since these methods vary in their input data, output labels, evaluation metrics, and sample coverage, the results presented in the table are intended to illustrate the general trends in methodological development, rather than to facilitate direct, numerical one-to-one comparisons. Stellar Atmospheric Parameters; Large Scale Spectroscopic Surveys; Deep Learning zhang yi xin JIAN GE PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank