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Crack Segmentation

Crack segmentation in computer vision involves identifying and delineating cracks or fractures in various types of surfaces, such as roads, pavements, walls, or infrastructure. This task is crucial for infrastructure maintenance, as it helps in assessing the condition of structures and planning repairs.

Papers

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Showing 31–40 of 63 papers

TitleStatusHype
Fine-tuning vision foundation model for crack segmentation in civil infrastructures—0
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation—0
Real-time High-Resolution Neural Network with Semantic Guidance for Crack SegmentationCode1
Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark DatasetCode0
TrueDeep: A systematic approach of crack detection with less data—0
Dual flow fusion model for concrete surface crack segmentation—0
A Few-Shot Attention Recurrent Residual U-Net for Crack SegmentationCode0
Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded ImagesCode1
A Convolutional-Transformer Network for Crack Segmentation with Boundary AwarenessCode1
Learning-Based Defect Recognitions for Autonomous UAV InspectionsCode2
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