Dataset for Crack Detection in Images of Masonry Using CNNs

We trained a convolutional neural network (CNN) on images of brick walls built in a laboratory environment and test its ability to detect cracks in images of brick-and-mortar structures both in the laboratory and on real-world images taken from the internet. We also compared the performance of the CNN to a variety of simple classifiers operating on handcrafted features. This is the dataset used in that work.