CONDITION ASSESSMENT OF RC BRIDGES. INTEGRATING MACHINE LEARNING, PHOTOGRAMMETRY AND BIM

18 citations as recorded by crossref.

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7. 3D Modeling & Analysis Techniques for the Apollo Temple in Delphi E. Maravelakis et al. https://doi.org/10.3390/buildings13071730
8. Application of Deep Learning Approach for the Classification of Buildings’ Degradation State in a BIM Methodology F. Rodrigues et al. https://doi.org/10.3390/app12157403
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10. Semantic Enrichment of BIM: The Role of Machine Learning-Based Image Recognition C. Mirarchi et al. https://doi.org/10.3390/buildings14041122
11. A deep learning-based pipeline for the conservation assessment of bindings in archives and libraries V. Lee-Gouet et al. https://doi.org/10.1007/s11042-025-20615-6
12. Synthetic Training Datasets for Architectural Conservation: A Deep Learning Approach for Decay Detection G. Patrucco et al. https://doi.org/10.3390/rs17101714
13. Smart Surveillance of Structural Health: A Systematic Review of Deep Learning-Based Visual Inspection of Concrete Bridges Using 2D Images N. Lotfi Karkan et al. https://doi.org/10.3390/infrastructures10120338
14. How to Digitise Bridge Structures—A Systematic Review of the Status Quo for Creating Digital BIM Models of Existing Bridge Structures in the Operational Phase J. Jäkel et al. https://doi.org/10.3390/infrastructures10030047
15. Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage R. Pierdicca et al. https://doi.org/10.3390/rs12061005
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