Automatic defect detection in infrared thermal images of ancient polyptychs based on numerical simulation and a new efficient channel attention mechanism aided Faster R-CNN model

Automatic defect detection in infrared thermal images of ancient polyptychs based on numerical simulation and a new efficient channel attention mechanism aided Faster R-CNN model

Abstract In recent years, the preservation and conservation of ancient cultural heritage necessitate the advancement of sophisticated non-destructive testing methodologies to minimize potential damage to artworks. Therefore, this study aims to develop an advanced method for detecting defects in anci...

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Bibliographic Details
Main Authors: Xin Wang, Guimin Jiang, Jue Hu, Stefano Sfarra, Miranda Mostacci, Dimitrios Kouis, Dazhi Yang, Henrique Fernandes, Nicolas P. Avdelidis, Xavier Maldague, Yonggang Gai, Hai Zhang
Format: Article
Language:English
Published: SpringerOpen 2024-09-01
Series:Heritage Science
Subjects:
Efficient channel attention
Faster R-CNN
Defect detection
Deep learning
Infrared thermography
Online Access:https://doi.org/10.1186/s40494-024-01441-9

Internet

https://doi.org/10.1186/s40494-024-01441-9

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