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

18 citations as recorded by crossref.

1. Defining a Digital Strategy in a BIM Environment to Manage Existing Reinforced Concrete Bridges in the Context of Italian Regulation A. Ciccone et al.
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7. 3D Modeling & Analysis Techniques for the Apollo Temple in Delphi E. Maravelakis et al.
8. Application of Deep Learning Approach for the Classification of Buildings’ Degradation State in a BIM Methodology F. Rodrigues et al.
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10. Semantic Enrichment of BIM: The Role of Machine Learning-Based Image Recognition C. Mirarchi et al.
11. A deep learning-based pipeline for the conservation assessment of bindings in archives and libraries V. Lee-Gouet et al.
12. Synthetic Training Datasets for Architectural Conservation: A Deep Learning Approach for Decay Detection G. Patrucco et al.
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.
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.
15. Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage R. Pierdicca et al.
16. Asset Management of Existing Concrete Bridges Using Digital Twins and BIM: a State-of-the-Art Literature Review V. Saback et al.
17. The Application of Historic Building Information Modelling (HBIM) to Cultural Heritage: A Review L. Lovell et al.
18. A Geospatially Enabled HBIM–GIS Framework for Sustainable Documentation and Conservation of Heritage Buildings B. Dammag et al.