Hardware deployment of deep learning model for classification of breast carcinoma from digital mammogram images.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 61; no. 11; pp. 2843 - 2858 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2023
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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=173036047&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 173036047 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Nov2023 vid: 61 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 173036047 167300011 10.1007/s11517-023-02883-2 173036047 ppf: 2843 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Hardware deployment of deep learning model for classification of breast carcinoma from digital mammogram images. aug: au: R, Kayalvizhi H, Heartlin Maria S, Malarvizhi Venkatraman, Revathi Patil, Shantanu affil: https://ror.org/050113w36 Department of Electronics and Communication, SRM Institute of Science and Technology, 603203, Kattankulathur, Chennai, India sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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