MFCR-SleepNet: A hard sample mining-based multi-scale featur…

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  • DOI 10.1016/j.neucom.2025.132399
  • OpenAlex ID W4417247066
  • Type Article
  • Language EN
  • Published 11 Dec 2025
  • Volume 668
  • Pages 132399
  • Source Neurocomputing
  • Publisher Elsevier BV
  • FWCI 0.57
  • Countries 2
  • Institutions 2
  • Added 11 Dec 2025
  • Updated 27 Oct 2026
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MFCR-SleepNet: A hard sample mining-based multi-scale feature contrastive representation learning model for sleep stage classification

Article 2025 EN

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0.57

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#AuthorInstitutionsORCID
1 Bohan Li Northwestern Polytechnical Uni… (CN)
2 Songyun Xie Corresponding Northwestern Polytechnical Uni… (CN)
3 Xinzhou Xie Corresponding Northwestern Polytechnical Uni… (CN)
4 Hao Tang Northwestern Polytechnical Uni… (CN)
5 Michael Scholz Technische Universität Berlin (DE)
6 Zhili Zhang Northwestern Polytechnical Uni… (CN)
7 Zhongyu Tian Northwestern Polytechnical Uni… (CN)
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