Dataset of cracks on DIC images

DOI10.5281/zenodo.4307686Zenodo4307686MaRDI QIDQ6696113

Dataset published at Zenodo repository.

Michele Godio, Katrin Beyer, Amir Rezaie, Radhakrishna Achanta

Publication date: 5 December 2020

Copyright license: Creative Commons Attribution 4.0 International

Description

This dataset contains crack images and corresponding annotated ground truth masks. This data was used to train, validate, and test a deep convolutional neural network to detect crack pixels on images taken as input for the digital image correlation (DIC) method. For more information about the trained network, please refer to our publication at this link. The source codes to reproduce the results are shared at this link. Please cite the following articles: [1] Rezaie, A., Achanta, R., Godio, M., Beyer, K. (2020). Comparison of crack segmentation using digital image correlation measurements and deep learning. Construction and Building Materials, 261, 120474.doi:https://doi.org/10.1016/j.conbuildmat.2020.120474 [2]Rezaie, A., Godio, M., Beyer, K. (2021). Investigating the cracking of plastered stone masonry walls under shearcompression loading.Construction and Building Materials,306, 124831. doi:https://doi.org/10.1016/j.conbuildmat.2021.124831

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