Crack detection and Wooden Artifacts Preservation System Based on Random Forest Classifier and WGAN-GP Network

YA CHUN CHOU

doi:https://doi.org/10.36463/idw.2023.1041

3:30 PM - 3:50 PM

[DES1-3L] Crack detection and Wooden Artifacts Preservation System Based on Random Forest Classifier and WGAN-GP Network

*YA CHUN CHOU¹, Chung Wen Hung¹ (1. National Yunlin University of Science and Technology (Taiwan))

defect detection, antiquities preservation, machine learning, WGAN-GP, random forest

https://doi.org/10.36463/idw.2023.1041

Defect detection with Machine learning algorithm is adopted to identify cracks on antiquities in this paper. Additionally, the WGAN-GP network is also adopted to generate defect samples for improving the results of machine learning. The experimental results show that the system is particularly effective, which can reach 0.95 for accuracy.

Proceedings of the International Display Workshops Volume 30 (IDW '23)

[DES1-3L] Crack detection and Wooden Artifacts Preservation System Based on Random Forest Classifier and WGAN-GP Network