The model achieved 92% accuracy than the single classifier and image processing methods in crack detection to monitor concrete structural health. Authors [22] used PCA (principal component analysis) ...

Detecting and analyzing cracks is crucial for assessing safety and determining maintenance needs. Various methods like image processing ... “Deep learning‐based crack damage detection using ...

This demo shows how to fine-tune a pretrained deep convolutional network called SqueezeNet [1] to perform a crack/normal image classification. The classification output was discussed using a technique ...

Their research confirmed that cracks might be detected and assessed using a damage index derived from ... while a CCD camera captured images. Through image processing (IP) techniques, the crack ...

At the same time, due to the scarcity of data, the existing tunnel lining surface crack detection methods still use multistep traditional image processing methods for ... the traditional U-shape ...

Therefore, this paper recommends using the U-Net model for crack detection. The U-Net model mainly extracts image feature information through down-sampling, maps the feature information to ...