Machine Learning for Structural Health Monitoring of Cultural Heritage

Informations projet

MLCULT

N° de convention de subvention: 101063722

DOI

10.3030/101063722

Projet clôturé

Date de signature de la CE 5 Mai 2022

Date de début 1 Juillet 2022

Date de fin 30 Novembre 2024

Financé au titre de

• Marie Skłodowska-Curie Actions (MSCA)

Coût total

Aucune donnée

Contribution de l’UE

€ 172 618,56

Coordonné par

UNIVERSIDADE DO MINHO
Portugal

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Livrables

Documents, reports (1)

Communication, Dissemination & Outreach Plan Description

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Data sets, microdata, etc (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected processed or generated by the action It is a document describing what data will be collected processed or generated and following what methodology and standards whether and how this data will be shared andor made open and how it will be curated and preserved

Publications

Peer reviewed articles (4)

Artificial intelligence-assisted visual inspection for cultural heritage: State-of-the-art review

Auteurs: Mayank Mishra, Paulo B. Lourenço
Publié dans: Journal of Cultural Heritage, 2024, ISSN 1778-3674
Éditeur: Elsevier
DOI: 10.1016/j.culher.2024.01.005

Internet of things (IoT)-based structural health monitoring of laboratory-scale civil engineering structures

Auteurs: T. Jothi Saravanan, Mayank Mishra, Abhishek Dilip Aherwar and Paulo B. Lourenço
Publié dans: Innovative Infrastructure Solutions, Numéro 9, 2024, ISSN 2364-4184
Éditeur: Springer
DOI: 10.1007/s41062-024-01413-9

Automated Surface Crack Detection in Historical Constructions with Various Materials Using Deep Learning-Based YOLO Network

Auteurs: Narges Karimi, Mayank Mishra, Paulo B Lourenco
Publié dans: International Journal of Architectural Heritage, 2024, ISSN 1558-3058
Éditeur: Taylor and Francis
DOI: 10.1080/15583058.2024.2376177

Deep learning-based automated tile defect detection system for Portuguese cultural heritage buildings

Auteurs: Narges Karimi, Mayank Mishra, Paulo B. Lourenco
Publié dans: Journal of Cultural Heritage, 2024, ISSN 1778-3674
Éditeur: Elsevier
DOI: 10.1016/j.culher.2024.05.009