A Novel Hybrid Transformer Approach for Text-Based Defect Classifications in the Construction Industry

In the construction industry, defects and their rework cause significant unplanned overheads. Defects are recorded in natural language, and while traditional manual evaluation and classification of defects is labor- and resource-intensive, transformer-based deep learning methods enable automated and...

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Bibliografiske detaljer

Principais autores:	Ricardo Buettner, Pascal Penava, Max Wiedemann
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2025-01-01
Serier:	IEEE Access
Fag:	Defect classification construction natural language processing machine learning deep learning transformer
Online adgang:	https://ieeexplore.ieee.org/document/11271422/
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