Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System.
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| Title: | Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System. |
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| Authors: | Jung, Jan Thomas1,2 (AUTHOR) alexander.reiterer@ipm.fraunhofer.de, Reiterer, Alexander1,2 (AUTHOR) |
| Source: | Sensors (14248220). Dec2024, Vol. 24 Issue 23, p7786. 32p. |
| 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: 181656149 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jung%2C+Jan+Thomas%22">Jung, Jan Thomas</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> alexander.reiterer@ipm.fraunhofer.de</i><br /><searchLink fieldCode="AR" term="%22Reiterer%2C+Alexander%22">Reiterer, Alexander</searchLink><relatesTo>1,2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sensors+%2814248220%29%22">Sensors (14248220)</searchLink>. Dec2024, Vol. 24 Issue 23, p7786. 32p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=181656149 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/s24237786 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 32 StartPage: 7786 Titles: – TitleFull: Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jung, Jan Thomas – PersonEntity: Name: NameFull: Reiterer, Alexander IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 14248220 Numbering: – Type: volume Value: 24 – Type: issue Value: 23 Titles: – TitleFull: Sensors (14248220) Type: main |
| ResultId | 1 |