Deep learning-based weathering type recognition in historical stone monuments
Bibliographic Data
| ID | 4644147 |
|---|---|
| Authors | Mehmet Ergün Hatir, M Ergün Hatır (Necmettin Erbakan University, corresponding author), Mücahit Barstuğan (Konya Technical University), Ismail Ince (0000-0002-6692-7584, Konya Technical University) |
| Year | 2020 |
| Volume | 45 |
| Pages | 193-203 |
| Publication date | 2020-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Cultural Heritage (JOURNAL) |
| Journal identifiers | ISSN: 1296-2074 • E-ISSN: 1778-3674 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.culher.2020.04.008 |
| OpenAlex | W3024043010 |
| Language | EN |
| Citations received | 15 |
| References cited | 58 |
Geochemistry · Weathering · 3D Surveying and Cultural Heritage · Building materials and conservation · Computer Science · Infrastructure Maintenance and Monitoring · Artificial Intelligence · Geology
Damage Types and Repair Techniques in Seljuk Period Stone Architectural Monuments
Research hotspots and trends in heritage building information modeling
Image Restoration for Heritage Photography Using Ai
Artificial Intelligence at the Interface between Cultural Heritage and Photography
A comprehensive review of deep learning methods in damage classification, detection, and segmentation of cultural heritage sites
Application of Object Detection Algorithm for Efficient Damages Identification of the Conservation of Heritage Buildings
Deep learning to detect built cultural heritage from satellite imagery. - Spatial distribution and size of vernacular houses in Sumba, Indonesia
Artificial intelligence-assisted visual inspection for cultural heritage
An object detection approach for detecting damages in heritage sites using 3-D point clouds and 2-D visual data
A Preliminary Study on the Social Organization Patterns of the Liangzhu Culture in the Northern Taihu Plain, China
Analysis of the Current Status of Sensors and HBIM Integration
Machine learning techniques for structural health monitoring of heritage buildings
Deep learning-based automated tile defect detection system for Portuguese cultural heritage buildings
The deep learning method applied to the detection and mapping of stone deterioration in open-air sanctuaries of the Hittite period in Anatolia
Deng entropy and LSTM neural network to classify built cultural heritage with severe damage
Deep learning in neural networks
ImageNet classification with deep convolutional neural networks
Deep learning
Multi-image 3D reconstruction data evaluation
The conservation state of the Sassi of Matera site (Southern Italy) and its correlation with the environmental conditions analysed through spatial analysis techniques
Unusual differential erosion related to the presence of endolithic microorganisms (Martvili, Georgia)
Determining the weathering classification of stone cultural heritage via the analytic hierarchy process and fuzzy inference system
Defining, mapping and assessing deterioration patterns in stone conservation projects
Evaluation of mechanical soft-abrasive blasting and chemical cleaning methods on alkyd-paint graffiti made on calcareous stones
Advanced damage detection techniques in historical buildings using digital photogrammetry and 3D surface anlysis
Fast, low cost and safe methodology for the assessment of the state of conservation of historical buildings from 3D laser scanning
| Unique citing works | 15 |
|---|---|
| Citations per year | 3 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 14 |