Search

Image Details

View Article Bookmark & Share

Choose export citation format:

Export Citation
Large resolution
Hi-Resolution Export to PDF PPT Format

An Improved Machine Learning Approach for Radio Frequency Interference Mitigation in FAST–SETI Survey Archival Data

  • Authors: Li-Li Zhao, Xiao-Hang Luan, Xin Chao, Yu-Chen Wang, Jian-Kang Li, Zhen-Zhao Tao, Tong-Jie Zhang, Hong-Feng Wang, Dan Werthimer

Li-Li Zhao et al 2026 The Astronomical Journal 171 .

  • Provider: AAS Journals

Caption: Figure 7.

Selected ETI candidates (33, black dots) and identified birdies (20, red dots) in the frequency (f)-time (t) plane, with other filtered hits shown in gray. The methodology’s effectiveness is demonstrated by the recovery of all 20 “birdies” and a final candidate count of 33 (e.g., 83 by Z.-S. Zhang et al. 2020; 31 by Y.-C. Wang et al. 2023).

Other Images in This Article
Image in this article
Image in this article
Image in this article
Image in this article
Image in this article
Image in this article
Image in this article
Copyright and Terms & Conditions

Additional terms of reuse