Deep Learning for the Segmentation of Large-Scale Surveys of Historic Masonry: A New Tool for Building Archaeology Applied at the Basilica of St Anthony in Padua-Reference-Cited by-同舟云学术

Deep Learning for the Segmentation of Large-Scale Surveys of Historic Masonry: A New Tool for Building Archaeology Applied at the Basilica of St Anthony in Padua

Published:2023-09-20 Issue: Volume: Page:1-13
ISSN:1558-3058
Container-title:International Journal of Architectural Heritage
language:en
Short-container-title:International Journal of Architectural Heritage

Author:

Vandenabeele Louis¹,Loverdos Dimitrios²,Pfister Marius¹,Sarhosis Vasilis²

Affiliation:

1. Institute for Preservation and Construction History (IDB), ETH Zurich, Zurich, Switzerland

2. School of Civil Engineering, University of Leeds, Leeds, UK

Funder

Swiss National Science Foundation

Publisher

Informa UK Limited

Subject

Visual Arts and Performing Arts,Architecture,Conservation

Link

https://www.tandfonline.com/doi/pdf/10.1080/15583058.2023.2260771

Reference39 articles.

1. PHOTOGRAMMETRY AS A TOOL FOR CHRONOLOGICAL DATING OF FIRED BRICKS STRUCTURES IN GENOA AREA

2. DAMAGE DETECTION AND LOCALIZATION IN MASONRY STRUCTURE USING FASTER REGION CONVOLUTIONAL NETWORKS

3. The Morphological Approach to Segmentation: The Watershed Transformation

4. Automated Defect Detection For Masonry Arch Bridges

5. Brackenbury, D., and M. Dejong. 2018. Mapping mortar joints in image textured 3D models to enable automatic damage detection of masonry arch bridges. 17th International Conference on Computing in Civil and Building Engineering, 173: 530–45. http://programme.exordo.com/icccbe2018/delegates/presentation/344/.

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1. Historic Built Environment Assessment and Management by Deep Learning Techniques: A Scoping Review;Applied Sciences;2024-08-13

2. Intelligent assessment system of material deterioration in masonry tower based on improved image segmentation model;Heritage Science;2024-07-23

3. Deep learning based approaches from semantic point clouds to semantic BIM models for heritage digital twin;Heritage Science;2024-02-21