Deterioration Detection in Historical Buildings with Different Materials Based on Novel Deep Learning Methods with Focusing on Isfahan Historical Bridges-Reference-Cited by-同舟云学术

Deterioration Detection in Historical Buildings with Different Materials Based on Novel Deep Learning Methods with Focusing on Isfahan Historical Bridges

Published:2023-04-16 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:

Karimi Narges¹^ORCID,Valibeig Nima¹^ORCID,Rabiee Hamid R.²^ORCID

Affiliation:

1. Architectural and Urban Conservation Department, Restoration and Conservation Faculty, Art University of Isfahan, Isfahan, Iran

2. Computer Engineering Department, Artificial Intelligent GroupDirector of AICT Research Institute, Director of Data Science and Artificial Intelligent Innovation Center, Sharif University of Technology, Tehran, Iran

Publisher

Informa UK Limited

Subject

Visual Arts and Performing Arts,Architecture,Conservation

Link

https://www.tandfonline.com/doi/pdf/10.1080/15583058.2023.2201576

Reference72 articles.

1. Real-time identification of disaster areas by an open-access vision-based tool

2. Evaluation of building materials using infrared thermography

3. Crack band theory for fracture of concrete

4. Image-processing technique to detect carbonation regions of concrete sprayed with a phenolphthalein solution

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automated masonry spalling severity segmentation in historic railway tunnels using deep learning and a block face plane fitting approach;Tunnelling and Underground Space Technology;2024-11

2. An Investigation of Historic Transportation Infrastructure Preservation and Improvement through Historic Building Information Modeling;Infrastructures;2024-07-18

3. Automated Surface Crack Detection in Historical Constructions with Various Materials Using Deep Learning-Based YOLO Network;International Journal of Architectural Heritage;2024-07-17

4. Method for Predicting Internal Defect Areas of Timber Components Based on an Adaptive Neuro-Fuzzy Inference System;International Journal of Architectural Heritage;2024-07-04

5. Deep learning-based automated tile defect detection system for Portuguese cultural heritage buildings;Journal of Cultural Heritage;2024-07