Deep learning for strong lensing search: tests of the convolutional neural networks and new candidates from KiDS DR3

@article{He2020DeepLF,
  title={Deep learning for strong lensing search: tests of the convolutional neural networks and new candidates from KiDS DR3},
  author={Zizhao He and Xinzhong Er and Qian Long and Dezi Liu and Xiangkun Liu and Ziwei Li and Yun Liu and Wenqaing Deng and Zu-hui Fan},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2020},
  volume={497},
  pages={556-571}
}
  • Zizhao He, X. Er, Z. Fan
  • Published 1 July 2020
  • Physics
  • Monthly Notices of the Royal Astronomical Society
Convolutional Neutral Networks have been successfully applied in searching for strong lensing systems, leading to discoveries of new candidates from large surveys. On the other hand, systematic investigations about their robustness are still lacking. In this paper, we first construct a neutral network, and apply it to $r$-band images of Luminous Red Galaxies (LRGs) of the Kilo Degree Survey (KiDS) Data Release 3 to search for strong lensing systems. We build two sets of training samples, one… 
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