2 papers
astro-ph.SR2026
Identify ~20,000 Li-rich Giants in the LAMOST Low-Resolution Survey
Ming-Yi Ding, Liang Wang, Jian-Rong Shi +8
Li-rich giants serve as valuable tracers of stellar evolution and surface enrichment processes, for which a statistically large and homogeneous sample is crucial. Using the massive…
astro-ph.GA2025
A robust morphological classification method for galaxies using dual-encoding contrastive learning and multi-clustering voting on JWST/NIRCam images
Xiaolei Yin, Guanwen Fang, Shiying Lu +3
The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To e…