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Space Selfies Level Up-AI Learns from the Best in the Universe
- Space Selfies Level Up-AI Learns from the Best in the Universe article discusses the construction of a Transformer model enhancing HST images to JWST quality.
- Training data sets consist of JWST-quality ground truth (GT) images and their degraded versions for model enhancement.
- Pre-training involves simplified galaxy images, while finetuning uses realistic galaxy images for the model.
- Different sets of training datasets are prepared to achieve the enhancement in image quality.
- GT and LQ images are generated using GalSim and HST point spread functions with added noise.
- HST Dataset includes multi-band galaxy images from HST/ACS deep fields like HUDF12, HUDFP2, GOODS-N&S fields.
- Sources are detected using SExtractor, with specific criteria for source selection and removal applied.
- Pre-training dataset creation by GalSim involves characterizing HST galaxies using elliptical Sersic parameters and fluxes.
- Elliptical Sersic profile modeling details are provided for characterizing HST galaxies for the model's pre-training.
- The article is available on arXiv under CC BY 4.0 Deed license for further reference.
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