A Fully Automated Deep Learning Pipeline for Anatomical Landmark Localization on Three-Dimensional Pelvic Surface Scans.
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| Title: | A Fully Automated Deep Learning Pipeline for Anatomical Landmark Localization on Three-Dimensional Pelvic Surface Scans. |
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| Authors: | Choi, Woosu1 (AUTHOR), Jang, Jun-Su1 (AUTHOR) junsu.jang@kiom.re.kr |
| Source: | Sensors (14248220). Mar2026, Vol. 26 Issue 6, p1760. 17p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 192598488 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Fully Automated Deep Learning Pipeline for Anatomical Landmark Localization on Three-Dimensional Pelvic Surface Scans. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Choi%2C+Woosu%22">Choi, Woosu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jang%2C+Jun-Su%22">Jang, Jun-Su</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> junsu.jang@kiom.re.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sensors+%2814248220%29%22">Sensors (14248220)</searchLink>. Mar2026, Vol. 26 Issue 6, p1760. 17p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192598488 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/s26061760 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1760 Titles: – TitleFull: A Fully Automated Deep Learning Pipeline for Anatomical Landmark Localization on Three-Dimensional Pelvic Surface Scans. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Choi, Woosu – PersonEntity: Name: NameFull: Jang, Jun-Su IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 14248220 Numbering: – Type: volume Value: 26 – Type: issue Value: 6 Titles: – TitleFull: Sensors (14248220) Type: main |
| ResultId | 1 |