Crossmark

Unsupervised multimodal deep learning for galaxy morphology taxonomy: integrating ConvNeXtEmbeddings and morphological parameters for scalable survey science

Crossref DOI link: https://doi.org/10.1038/s41598-026-45369-5

Published Online: 2026-04-11

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Selim, I. M.

Farahat, Ahmed S.

Basmsm, Lobna H.

El-Hameed, Afaf M. Abd
Funding

Funding for this research was provided by:

The National Research Institute of Astronomy and Geophysics
License Information

Text and Data Mining valid from 2026-04-11

Version of Record valid from 2026-04-13
More Information

Article History

Received: 3 December 2025

Accepted: 18 March 2026

First Online: 11 April 2026

Declarations

:

: The authors declare no competing interests.

Document is current

Any future updates will be listed below