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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

Showing 1120 of 63 papers

TitleStatusHype
DSCformer: A Dual-Branch Network Integrating Enhanced Dynamic Snake Convolution and SegFormer for Crack Segmentation0
Multi-temporal crack segmentation in concrete structure using deep learning approaches0
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks0
Topology-aware Mamba for Crack Segmentation in StructuresCode1
Benefiting from Quantum? A Comparative Study of Q-Seg, Quantum-Inspired Techniques, and U-Net for Crack Segmentation0
Distribution-aware Noisy-label Crack SegmentationCode0
CrackSegDiff: Diffusion Probability Model-based Multi-modal Crack SegmentationCode1
IRFusionFormer: Enhancing Pavement Crack Segmentation with RGB-T Fusion and Topological-Based LossCode1
EfficientCrackNet: A Lightweight Model for Crack Segmentation0
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil InfrastructureCode2
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