Deep Learning in the Architecture, Engineering, and Construction (AEC) Industry: Methods, Challenges, and Emerging Opportunities.
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| Title: | Deep Learning in the Architecture, Engineering, and Construction (AEC) Industry: Methods, Challenges, and Emerging Opportunities. |
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| Authors: | Khan, Muhammad Imran1, Waheed, Abdul2, Harirchian, Ehsan3, ehsan.harirchian@uni-weimar.de, Manzoor, Bilal4 |
| Source: | Buildings (2075-5309); Apr2026, Vol. 16 Issue 8, p1546, 24p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 193440916 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/buildings16081546 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 1546 Titles: – TitleFull: Deep Learning in the Architecture, Engineering, and Construction (AEC) Industry: Methods, Challenges, and Emerging Opportunities. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khan, Muhammad Imran – PersonEntity: Name: NameFull: Waheed, Abdul – PersonEntity: Name: NameFull: Harirchian, Ehsan – PersonEntity: Name: NameFull: Manzoor, Bilal IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20755309 Numbering: – Type: volume Value: 16 – Type: issue Value: 8 Titles: – TitleFull: Buildings (2075-5309) Type: main |
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