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- Crack detection is a critical task in monitoring and inspection of civil engineering structures. Image classification and bounding box approaches have been proposed in existing vision-based automated concrete crack detection methods using deep convolutional neural networks.
Author: Cao Vu Dung, Le Duc AnhPublish Year: 2019www.sciencedirect.com/science/article/pii/S0926580518306745 Deep neural networks for crack detection inside structures
Feb 23, 2024 · We found that a robust backbone network, such as Densely Connected Convolutional Network (DenseNet) can effectively extract the features characterizing cracks of …
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A novel convolutional neura…
However, traditional convolutional neural networks often struggle with issues such …
Structural crack detection using deep convolutional neural networks
Jan 1, 2022 · CrackNet-V based on a deep neural network is proposed [140] for pixel-level crack detection. The method determines a specific pixel in a particular region on a 3D asphalt …
- Author: Raza Ali, Raza Ali, Joon Huang Chuah, Mohamad Sofian Abu Talip, Norrima Mokhtar, Muhammad Ali Shoaib...
- Publish Year: 2022
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Autonomous concrete crack detection using deep fully …
Mar 1, 2019 · Crack detection is a critical task in monitoring and inspection of civil engineering structures. Image classification and bounding box approaches have been proposed in existing …
- Author: Cao Vu Dung, Le Duc Anh
- Publish Year: 2019
A novel convolutional neural network for enhancing the continuity …
Dec 5, 2024 · However, traditional convolutional neural networks often struggle with issues such as missed detection and false detection when extracting cracks. This paper introduces a …
Road crack detection using deep convolutional neural …
Aug 19, 2016 · Inspired by recent success on applying deep learning to computer vision and medical problems, a deep-learning based method for crack detection is proposed in this paper. A supervised deep convolutional neural network is …
GitHub - alexwcheng/crack-detection: A CNN …
So to make life easier, an automated tool powered by a Convolutional Neural Network (CNN) can help detect obviously deficient work for us - in particular, cracking. This tool is not intended to replace manual review of construction …
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NB-CNN: Deep Learning-Based Crack Detection …
Oct 19, 2017 · This study proposes a deep learning framework, based on a convolutional neural network (CNN) and a Naïve Bayes data fusion scheme, called NB-CNN, to analyze individual video frames for crack detection while a …
Image‐Based Concrete Crack Detection Using …
Apr 30, 2019 · To overcome these challenges, this paper proposes an image-based crack detection method using a deep convolutional neural network (CNN). A CNN is designed through modifying AlexNet and then trained and validated …
Road Crack Detection Using Deep Convolutional Neural Network …
Apr 18, 2019 · In this paper, we propose a novel road crack detection algorithm based on deep learning and adaptive image segmentation. Firstly, a deep convolutional neural network is …
Concrete-Crack-Detection-Segmentation - GitHub
This repository contains the code for crack detection on concrete surfaces. It is a PyTorch implementation of Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks with DeepCrack. DeepCrack: A Deep …
Bicrack: a bilateral network for real-time crack detection
Nov 5, 2024 · To solve the above problems, a novel bilateral crack detection network (BiCrack) is proposed for real-time crack detection tasks. Specifically, the network fuses two feature …
CrackU‐net: A novel deep convolutional neural network for …
Mar 18, 2020 · Therefore, this research proposes a state-of-the-art pixelwise crack detection architecture called CrackU-net, which is featured by its utilization of advanced deep …
Deep Learning‐Based Crack Damage Detection Using …
Mar 23, 2017 · To overcome these challenges, this article proposes a vision-based method using a deep architecture of convolutional neural networks (CNNs) for detecting concrete cracks …
Deep neural networks for crack detection inside structures
The current trend of crack detection emphasizes using deep neural networks to build an automated pipeline from measured signals to damaged areas. This work focuses on the …
Manual inspection of cracks on concrete surfaces requires wholesome knowledge and depends entirely on the expertise and capabilities of the inspector. This study proposes the use of a …
Crack Detection and Classification in Asphalt Pavement Images …
Experimental results show that deep CNN using 32x32 grid scale images provides higher performance for crack detection and classification compared to 64x64.
We found that a robust backbone network, such as Densely Connected Convolutional Network (DenseNet) can efectively extract the features characterizing cracks of wave signals, and by...
Fast Crack Detection Using Convolutional Neural Network
May 23, 2021 · For three different objectives: 1) Detection of the concrete cracks; 2) Detection of natural stone cracks; 3) Differentiation between joints and cracks in natural stone; We built a …
Crack identification of concrete structures based on high-precision ...
Liu [13] proposed an apparent defect detection system for precast concrete components, firstly, the images were preprocessed to filter out the noise and interference on the surface of the …
Enhancing structural health monitoring with AI-ML algorithms
2 days ago · The crack detection and prediction analysis provided valuable information about the relationship between crack-specific features, environmental factors, and structural integrity. …
Deep neural networks for crack detection inside structures
Feb 23, 2024 · We found that a robust backbone network, such as Densely Connected Convolutional Network (DenseNet) can effectively extract the features characterizing cracks of …
Convolutional neural networks-based crack detection for real …
Mar 27, 2018 · Through integrating the trained CNN classifier into a smartphone application, the detection of crack in an image can be implemented automatically. The results illustrate that the …
Deepfake Detection of Face Images based on a Convolutional …
Mar 14, 2025 · Abstract page for arXiv paper 2503.11389: Deepfake Detection of Face Images based on a Convolutional Neural Network. Fake News and especially deepfakes (generated, …
Recurrent Neural Networks for Temporal Analysis in Cancer …
1 day ago · Convolutional Neural Networks (CNNs) have been widely used in static image analysis, yielding high accuracy in detecting tumors in medical images. ... et al. (2016). …
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