I have used the following methods.

• Dice coefficient implementation,
• Custom layers for encoding and decoding,
• Custom callback class that used predicting a sample from the test dataset during training

1. [Dataset] Sabouri, Mohammadreza; Sepidbar, Alireza (2023), “SUT-Crack”, Mendeley Data, V5, doi: 10.17632/gsbmknrhkv.5
2. Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation https://doi.org/10.48550/ARXIV.1505.04597