There are two stitching methods used to repair and strengthen cracks or joints in concrete pavement. The first, and most common, is cross-stitch-ing. Cross-stitching uses deformed …
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However, in practical application, the road background 2 Wireless Communications and Mobile Computing. is complex and there are many noises, so there are few algo- ... and use the classification technology of machine learning to detect the crack pavement automatically. Hu et al. [25] pro-posed a new automatic crack pavement detection method
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main categories of cracks that can be detected in early pavement deterioration are trans-verse, longitudinal, block, and alligator [7,8]. The existence of pavement cracks will acceleratethe deterioration of the pavement, and restoring these cracks can result in higher maintenance costs. Delays in maintenance . Citation: Wang, Y.; Qi, Q.; Sun, L.;
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There are two stitching methods used to repair and strengthen cracks or joints in concrete pave-ment. The first, and most common, is cross-stitching. Cross-stitching uses deformed tie bars …
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Semantic Scholar extracted view of "Chronological development history of X–Y table based pavement crack sealers and research findings for practical use in the field" by Y. S. Kim et al. ... Development of an Automated Pavement Crack Sealing Machine and Its Economic Feasibility Analysis. Jeong-ho Lee Junbok Lee Hyemi Jeong Young-Suk Kim.
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Throughout recent decades, pavement surface crack detection has evolved with the following stages: (1) Manual Detection.This refers to visual detection of the pavement surface by crews, which requires individuals to be on the site to look for cracks and make corresponding judgements [2].This method is time-consuming, labor-intense, and may cause safety concerns.
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Pavement crack image acquisition methods and crack extraction algorithms: A review ... which makes it difficult to meet the practical needs. The research on automatic recognition of pavement damage image in the world mainly focuses on the hardware of pavement image acquisition system, but the pavement damage 2D image processing has been a ...
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Computer Vision-Based Recognition of Pavement Crack Patterns Using Light Gradient Boosting Machine, Deep Neural Network, and Convolutional Neural Network January 2023 DOI: 10.22115/SCCE.2023. ...
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Crack sealing has two primary purposes: To prevent the intrusion of water through the crack into the underlying pavement structure. To prevent extraneous materials from …
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However, existing approaches utilize complex network structures which, while improving accuracy, compromise detection efficiency and hinder practical application. This paper proposes a novel pixel-level pavement crack segmentation model, RepCrack, which addresses the current limitations in accuracy and efficiency in pavement crack detection tasks.
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Effective road pavement management is vital for maintaining the functionality and safety of transportation infrastructure. This review examines the integration of Machine Learning (ML) into Pavement Management Systems (PMS), presenting an analysis of state-of-the-art ML techniques, algorithms, and challenges for application in the field. We discuss the limitations of …
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16, pavement cracks were classified by applying different machine learning algorithms, such as the support vector machine, random forest and ANN. 17, longitudinal and transverse cracks were detected and classified by implementing image processing techniques and ANN, where the images were acquired through ARAN.
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Measuring the geometric properties of pavement cracks using chessboard calibration and Inverse Perspective Mapping. The method uses an on-vehicle camera and can be applied to other …
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There are two stitching methods used to repair and strengthen cracks or joints in concrete pavement. The first, and most common, is cross-stitching. Cross-stitching uses deformed tiebars epoxied or grouted into holes drilled at an angle through a crack. The second, slot-stitching, uses deformed tiebars grouted into slots cut across a joint or ...
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The DL algorithms represented by Convolutional Neural Networks (CNN) can directly learn features from massive original crack images without a tedious preprocessing process, showing considerably faster operation and accessibility [38]pared to traditional ML algorithms, CNN algorithms have been prevalent in the task of pavement condition monitoring …
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The process involves using a large industrial pavement routing machine to grind a channel through the centre of the crack where the sealant is to be injected. Prior to doing so, field workers must first thoroughly clear out all debris, leaves, sticks and other obstructive objects from the surrounding area that might interfere with the sealing ...
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These contributions collectively advance the state of the art in asphalt pavement crack detection, offering a more effective and accurate approach, particularly for addressing challenges related to small and shallow crack detection, accuracy improvement, and attention focusing on the image.
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The machine heats the crack filler material to the required temperature and pumps it through the wand or hose for precise application into the cracks. Melter/applicator machines are commonly used by professional contractors …
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In slot-stitching, slots with lengths no smaller than 25 inches are cut approximately perpendicular to the longitudinal joints or cracks using a slot cutting machine or walk-behind saw. Slots are prepared by removing the concrete and cleaning the slot. Deformed bars are placed and backfill material is applied, finished, and cured.
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Pavement crack images were acquired using an on-vehicle camera, and a semi-automatic annotation method was used to generate the dataset. ... The algorithm presented in this paper holds practical value and can serve as a reference and inspiration for feature segmentation problems in other fields. ... Deep machine learning approach to develop a ...
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In this study, DSFRRN was proposed to segment pavement crack. A self-constructed dataset of 1565 pavement crack was used to evaluate and compare the proposed model with other comparative models. Figure 6 shows that the proposed method has the fastest loss reduction and also the smallest loss at convergence.
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Table 1 briefly describes the accomplishments and major limitations of previous research works. The hardware of early x–y table based pavement crack sealing systems was incomplete in the early stage. At the same time, the software for mapping and modeling the crack network to be sealed and path planning were not efficient in terms of productivity, quality, and …
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This paper discusses a machine vision system that is used to find pavement cracks for a robotic crack sealing machine. The system includes a high-resolution digital camera …
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In slot-stitching, slots with lengths no smaller than 25 inches are cut approximately perpendicular to the longitudinal joints or cracks using a slot …
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Accurate pavement surface crack detection is crucial for analyzing pavement survey data and the development of maintenance strategies. On the basis of Swin-Unet, this study develops the improved Swin-Unet (iSwin-Unet) model with the developed skip attention module and the residual Swin Transformer block. Based on the channel attention mechanism, …
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AigleRN [26] is a grayscale crack image dataset of road pavement in France, including 38 images. Half of this dataset is sized 991 × 462 pixels, while the other half is 311 × 462 pixels. CRACK500 [171] and [15] is a dataset consisting of 500 pavement cracks images. All images in this dataset are collected using a smartphone.
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Cracks are one of the most common asphalt pavement distresses. According to morphological characteristics, cracks can be divided into alligator cracks, block cracks, longitudinal cracks, and transverse cracks (in Fig. 2), with different degrees of crack damage (light, medium, and heavy), according to the Chinese specification as shown in Table 1 (JTG, …
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The cement concrete pavement irregular crack slotting machine can slot in the newly constructed cement pavement or the irregular cracks of the prior cement pavement and asphalt pavement.
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2. Cut the slots. Once the need for DBR is established, the next step is to cut the slots using a diamond saw slot cutter. It is customary to provide three dowel bars in each wheel path. The diamond saw slot cutter shown in Figure 10-18 cuts multiple slots in a single pass.
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The rise of machine learning and deep learning, as well as the introduction of convolutional neural network (CNN), is a major breakthrough in the computer vision (CV) [12], [13], [14], [15].CNN can extract image features very well, so many excellent algorithms have been proposed for crack detection [16], [17].For example, Choi et al. [18] proposed SDDNet for real …
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This paper presents a novel multi-initialization model for recognizing road surface damage, e.g. potholes and cracks, on video using convolutional neural networks (CNNs) in real-time for fast damage recognition. The model is trained by the latest Road Damage Detection dataset, which includes four types of road damage. In addition, the CNN model is updated …
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Image-based pavement crack detection methods can be categorized into two types: digital image processing [[3], [4], [5]] and deep learning [[6], [7], [8]]. Digital image processing encompasses edge detection and thresholding algorithms, which can be practical solutions for detecting crack edges. By analyzing the images, we can extract edge ...
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