Surface Crack Detection is a machine learning project aimed at automatically identifying cracks on surface images.
Confusion Matrix
- Data Preprocessing: Loading, resizing, and normalizing images.
- Model Training: Development and training of a CNN for image classification.
- Model Evaluation: Assessing model performance with metrics and visualizations.
- Image Classification Uploading and classifying
The dataset comprises images categorized into two classes:
- Positive: Images containing surface cracks.
- Negative: Images without surface cracks.
Özgenel, Çağlar Fırat (2019), “Concrete Crack Images for Classification”, Mendeley Data, V2, doi: http://dx.doi.org/10.17632/5y9wdsg2zt.2x