Adversarial attacks and adversarial training for burn image segmentation based on deep learning.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 62; no. 9; pp. 2717 - 2736 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2024
|
| 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=179087852&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179087852 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2024 vid: 62 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 179087852 176919732 10.1007/s11517-024-03098-9 179087852 ppf: 2717 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Adversarial attacks and adversarial training for burn image segmentation based on deep learning. aug: au: Chen, Luying Liang, Jiakai Wang, Chao Yue, Keqiang Li, Wenjun Fu, Zhihui affil: https://ror.org/0576gt767 Zhejiang Integrated Circuits and Intelligent Hardware Collaborative Innovation Center, Hangzhou Dianzi University, 317300, Hangzhou, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|