G-T correcting: an improved training of image segmentation under noisy labels.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 62; no. 12; pp. 3781 - 3800 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180936633&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180936633 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2024 vid: 62 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 180936633 10.1007/s11517-024-03170-4 180936633 ppf: 3781 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: G-T correcting: an improved training of image segmentation under noisy labels. aug: au: Gao, Yun Fu, Junhu Guo, Yi Wang, Yuanyuan affil: School of Information Science and Technology of Fudan University, 220 Handan Rd, 200433, Shanghai, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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