Transformer in galaxy: a study of galaxy classification based on the Swin transformer

Zhenyu Huang

doi:10.1117/12.2667869

28 March 2023 Transformer in galaxy: a study of galaxy classification based on the Swin transformer

Zhenyu Huang

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125661E (2023) https://doi.org/10.1117/12.2667869
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

By replicating the CNN part of Galnet network and inspired by Swin Transformer, the article constructs a Transformer-based model called SwinT Galnet by adding the Swin Transformer block into Galnet thus introduces the attention mechanism into that traditional model, trying to investigate the improvement of Transformer over CNN in a single Sérsic galaxy model data. This article compares Sérsic parameters of SwinT with those of CNN. The paper compares the parameters trained by Galnet and SwinT Galnet and shows that the Transformer has an improvement by calculating global attention in accuracy over the pure CNN-based network in galaxy parameters regression tasks, indicates that Transformer has a large potential in the field of galaxy morphology.

Citation Download Citation

Zhenyu Huang "Transformer in galaxy: a study of galaxy classification based on the Swin transformer", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125661E (28 March 2023); https://doi.org/10.1117/12.2667869

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KEYWORDS

Galactic astronomy

Transformers

Education and training

Data modeling

Point spread functions

Convolution

Performance modeling

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