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   Articles with "crack segmentation" as a keyword



Concrete roadway crack segmentation using encoder-decoder networks with range images

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recommendations! Published in 2020 at "Automation in Construction"

DOI: 10.1016/j.autcon.2020.103403

Abstract: Abstract Recently, researchers have utilized DCNN for pixel-wise crack classification through semantic segmentation. Nevertheless, some issues in current DCNN-based roadway crack segmentation are yet to be fully addressed. For example, image pre-processing techniques are often… read more here.

Keywords: crack segmentation; methodology; encoder decoder; roadway crack ... See more keywords

A lightweight crack segmentation network based on the importance-enhanced Mamba model

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-25504-4

Abstract: In the maintenance of transportation infrastructure, crack segmentation is critical for ensuring road safety and prolonging the service life of bridges and other facilities. Existing methods struggle with complex background interference and intricate crack morphologies… read more here.

Keywords: segmentation; crack; model; crack segmentation ... See more keywords

Automated high-resolution asphalt pavement crack segmentation using deep convolutional neural networks with repeated hierarchical feature fusion

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recommendations! Published in 2024 at "International Journal of Pavement Engineering"

DOI: 10.1080/10298436.2024.2402838

Abstract: ABSTRACT Automated collection and detection of asphalt pavement crack conditions are essential for evaluating road conditions and maintenance planning. However, determining crack conditions accurately and efficiently has been challenging due to their small object-to-background information… read more here.

Keywords: resolution asphalt; asphalt pavement; pavement crack; crack ... See more keywords
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Fine-tuning large vision model for multimodal fusion in asphalt pavement crack segmentation

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recommendations! Published in 2025 at "International Journal of Pavement Engineering"

DOI: 10.1080/10298436.2025.2526158

Abstract: ABSTRACT Automated high-precision crack detection in asphalt pavements is vital for road safety and infrastructure longevity. However, existing RGB-based models are often affected by environmental interference, and limited training datasets hinder their generalisation. To address… read more here.

Keywords: segmentation; asphalt; crack; large vision ... See more keywords

Enhancing Crack Segmentation With Limited Data: SinGAN-Based Synthesis and Blending of Textures and Cracks

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3576335

Abstract: The reliable detection of structural cracks is crucial in maintaining the integrity of different structures like pipes and pavements, yet it is often constrained by the limited availability of diverse training datasets. This research presents… read more here.

Keywords: detection; segmentation; crack; crack segmentation ... See more keywords

DSCP-UNet: A Tunnel Crack Segmentation Algorithm Based on Lightweight Diminutive Size and Colossal Perception

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3617337

Abstract: To effectively enhance the ability to detect surface crack defects in tunnels under tunnel conditions, this paper proposes a new tunnel crack segmentation algorithm using light-weight diminutive size and colossal perception UNet (DSCP-UNet). This method… read more here.

Keywords: crack; tunnel crack; dscp unet; crack segmentation ... See more keywords

Highway Crack Segmentation From Unmanned Aerial Vehicle Images Using Deep Learning

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recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2021.3129607

Abstract: Highway crack segmentation is a critical task for highway infrastructure monitoring and maintenance. While imagery from unmanned aerial vehicles (UAVs) is applied to the task of highway crack segmentation, it has great prospects in terms… read more here.

Keywords: road; crack; segmentation; highway crack ... See more keywords
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V2net: A Nested Framework for Crack Segmentation Based on Multiscale Feature Learning

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recommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2025.3550234

Abstract: Crack detection is crucial for infrastructure safety assessment and maintenance. However, the diversity of crack patterns, complex topologies, and variable imaging conditions pose significant challenges to automatic segmentation systems. In addition, issues with multiscale feature… read more here.

Keywords: segmentation; crack; crack segmentation; multiscale feature ... See more keywords

Joint Optimization of Crack Segmentation With an Adaptive Dynamic Threshold Module

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recommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2023.3348812

Abstract: Crack segmentation is a critical component in structural health monitoring. Conventional crack segmentation models usually focus on optimizing the cross-entropy-based objective function and overlook the optimization of the subsequent binarization process. In this paper, we… read more here.

Keywords: adaptive dynamic; segmentation; crack; crack segmentation ... See more keywords

Teaching Segment-Anything-Model Domain-Specific Knowledge for Road Crack Segmentation From On-Board Cameras

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recommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2024.3475371

Abstract: Road crack segmentation from on-board cameras is a highly desirable yet challenging task for road condition inspection and maintenance. However, existing methods trained on small-scale datasets present limited performance from such challenging perspectives due to… read more here.

Keywords: crack; road; board cameras; crack segmentation ... See more keywords

A Novel Proactive Fault Tolerance Loss Function for Crack Segmentation

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recommendations! Published in 2025 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2025.3525527

Abstract: Optimizing the generalization performance of road surface crack models in practical applications represents a challenging task. Especially for thin and irregular cracks with random and expansive topologies, the loss functions used in current deep learning-based… read more here.

Keywords: loss; proactive fault; crack; fault tolerance ... See more keywords