<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

The data for Galaxy-Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting 2-Dimensional Information from Multi-Band Images in Ground and Space Observations

Name: The data for Galaxy-Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting 2-Dimensional Information from Multi-Band Images in Ground and Space Observations
Creator: Fucheng, Zhong

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 07 Dec 2024Publisher:Zenodo

Authors: Fucheng, Zhong;

doi: 10.5281/zenodo.14294633 , 10.5281/zenodo.14294634

The data for Galaxy-Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting 2-Dimensional Information from Multi-Band Images in Ground and Space Observations

- Summary
- Metrics

Abstract

GGSL-UNet v1.0.0 Release v1.0.0 Code and data for "Galaxy-Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting 2-Dimensional Information from Multi-Band Images in Ground and Space Observations" (https://arxiv.org/abs/2410.02936) A demo of GGLS-UNet: 1. Training model $ python diffusion_model.py 2. The demonstration of reconstruction - see prediction.ipynb 3. Files and data - color_images.fits : the mock KiDS images.- results/kids_lens.fits : the KiDS lens candidates and reconstructed images.- GGL_UNet_diffusion_model : pre-trained model, the model weights file. ## If you used the code here, please cite our paper Zhong et al. 2024. Publisher Information Creator: Fucheng ZhongEmail: zhongfch@mail2.sysu.edu.com

Related Organizations

Sun Yat-sen University
China (People's Republic of)

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

Average