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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 41–50 of 63 papers

TitleStatusHype
Robust feature knowledge distillation for enhanced performance of lightweight crack segmentation models—0
Deep Learning for Segmentation of Cracks in High-Resolution Images of Steel Bridges—0
A statistical method for crack detection in 3D concrete images—0
Mind Marginal Non-Crack Regions: Clustering-Inspired Representation Learning for Crack Segmentation—0
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
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
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