In this paper, the performance of five deep learning models, including a proposed customized CNN model, were evaluated for crack detection and localization in concrete structures using …

Jan 1, 2022 · The first way of crack detection through CNN architecture is a sliding window technique and the second method is pixel-level crack detection. We investigated both parts …

A Deep Convolutional Neural Network model to detect crack on a concrete/metal surface through its image. Built in Jupyter Python Notebook on Google Colaboratory using Keras from …

I analyzed confusion matrix results of the CNN models, then determined accuracy, precision, recall, and F1 score metrics. Next, I plotted prediction probabilities for each type of …

May 27, 2023 · Although in a convolutional neural network and naïve Bayes data fusion scheme were proposed for crack detection in nuclear power plant components, this NB-CNN algorithm …

The testing results suggest that ResNet and DenseNet are the best options for crack classification, while Faster R-CNN should be used for crack object detection and pix2pix is …

Thus, in this study, shallow convolutional neural network (CNN)-based architecture for surface concrete crack detection is proposed. LeNet-5, a well-known CNN architecture, is optimized …

This work first time strives to classify concrete surface cracks by re-training of six pre-trained deep CNN models such as VGG-16, DenseNet-121, Inception-v3, ResNet-50, Xception, and ...

Civil engineering crack detection faces challenges due to complex environments and external interferences. This paper proposes an improved YOLO v8s-WOMA network, integrating …

Jan 23, 2021 · In this study, a shallow CNN-based architecture is employed for concrete surface crack detection. The entire procedure of the proposed method consists of fine-tuning of the …