Semi-supervised multi-source transfer learning for cross-subject EEG motor imagery classification.

Bibliographic Details
Published in:Medical & Biological Engineering & Computing Vol. 62; no. 6; pp. 1655 - 1673
Main Authors: Zhang, Fan, Wu, Hanliang, Guo, Yuxin
Format: Journal Article
Published: Springer Nature Jun2024
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=177078976&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 177078976
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01400118
        PO0
      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
      maglogo: N
    pubinfo:
      dt: Jun2024
      vid: 62
      iid: 6
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        177078976
        175292805
        10.1007/s11517-024-03032-z
        177078976
      ppf: 1655
      ppct: 18
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Semi-supervised multi-source transfer learning for cross-subject EEG motor imagery classification.
      aug:
        au:
          Zhang, Fan
          Wu, Hanliang
          Guo, Yuxin
        affil: https://ror.org/02xe5ns62 Jinan University, Guangzhou, China
      sug:
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N