4IPLAY - Improving Intelligent Infrastructure Inspection by Pushing UAS Level of Autonomy in Challenging Environments-Reference-Cited by-同舟云学术

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4IPLAY - Improving Intelligent Infrastructure Inspection by Pushing UAS Level of Autonomy in Challenging Environments

Published:2024-06-03 Issue: Volume:347 Page:278-283
ISSN:
Container-title:2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace)
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Author:

Mancini Adriano¹,Galdelli Alessandro¹,Capello Elisa²,Du Mutel de Pierrepont Franzetti Iris David²,Primatesta Stefano²,Fasano Giancarmine³,Opromolla Roberto³,Causa Flavia³,Vitiello Federica³

Affiliation:

1. Università Politecnica delle Marche,VRAI Lab,Department of Information Engineering,Ancona,Italy

2. Politecnico di Torino,Department of Mechanical and Aerospace Engineering,Torino,Italy

3. Università di Napoli “Federico II”,Department of Industrial Engineering,Napoli,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10591476/10591509/10591600.pdf?arnumber=10591600

Reference23 articles.

1. A comparison between computer vision- and deep learning-based models for automated concrete crack detection

2. Deep learning-based concrete defects classification and detection using semantic segmentation

3. Image-Based Corrosion Detection in Ancillary Structures

4. Multiclass Anomaly Detection of Bridge Monitoring Data with Data Migration between Different Bridges for Balancing Data

5. Towards fully automated unmanned aerial vehicle-enabled bridge inspection: Where are we at?;Zhang;Construction and Building Materials,2022

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