Morphology classification for galaxies in the Kilo Degree Survey using a label-efficient self-supervised learning framework

arXiv:2609.21705 · astro-ph.GA · Submitted 2026-09-18 · Read on arXiv

astro-ph.GA

Submitted: 2026-09-18

Updated: 2026-09-18

Comments: 20 pages, 9 figures

DOI: 10.3847/1538-4365/aea210

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 3× in this paper · explained in 1 episode
• Self-Supervised Learning — 3× in this paper · explained in 8 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• F1 Score — 1× in this paper · explained in 3 episodes

Related papers

• Apparent Stability in Self-Gravitating Turbulence and the Evolution of Molecular Clouds
• Two sets of potential-density basis pairs for the study of radial perturbations in collisionless spherical stellar systems
• Constraining reionization-era Ly alpha escape with JELS-MUSE: a highly complete H alpha-selected sample at z about6.1
• Deriving volume density profiles of filaments from observed surface densities
• Little Red Dots and Supermassive Black Hole Seed Formation in Ultralight Dark Matter Halos
• MEGATRON: how the first stars can create an iron metallicity plateau in the smallest dwarf galaxies