Structural and Photometric Parameter Estimation of Low-surface-brightness Galaxies Using a Deep Learning Framework

Low-surface-brightness galaxies (LSBGs) play an important role in studies of galaxy formation and evolution, yet accurate measurements of their structural and photometric parameters remain challenging for conventional analysis pipelines due to their diffuse light distributions and low signal-to-nois...

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Autors principals:	Yewang Zhang, Zhenping Yi, Zheyun Qin, Wei Du, Rui Li, Meng Liu, Yude Bu, Dong Li
Format:	Artigo
Idioma:	Inglês
Publicat:	IOP Publishing 2026-01-01
Col·lecció:	The Astrophysical Journal Supplement Series
Matèries:	Low surface brightness galaxies Neural networks Galaxy formation Galaxy structure Convolutional neural networks
Accés en línia:	https://doi.org/10.3847/1538-4365/ae7b29
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