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This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
Visual crack detection
Dataset acquired from https://digitalcommons.usu.edu/all_datasets/48/
About this project
Visual Anomaly Detection (FOMO-AD)
Read more about FOMO-AD here: https://docs.edgeimpulse.com/docs/edge-impulse-studio/learning-blocks/visual-anomaly-detection
Dataset: https://digitalcommons.usu.edu/all_datasets/48/
Maguire, M., Dorafshan, S., & Thomas, R. J. (2018). SDNET2018: A concrete crack image dataset for machine learning applications. Utah State University. https://doi.org/10.15142/T3TD19
Run this model
On any device
Dataset summary
Data collected
1,308 itemsLabels
nominalProject info
Project ID | 288658 |
License | BSD 3-Clause Clear |
No. of views | 69,959 |
No. of clones | 29 |