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Fractal Knowledge-Guided Diffusion Representation Learning Framework for Self-supervised Crack Segmentation
DOI:10.1016/j.knosys.2026.116085.png)
摘要
En 中文
• 分形伪掩码与拓扑引导无标签数据的学习。
• 多尺度门控扩散模块改进裂缝特征建模。
• 双流空间自适应反归一化稳定对抗训练。
• 对比无配对翻译实现对比表示学习。
Keyword:
Fractal pseudo-masks
Multi-scale gated diffusion
Dual-stream spatially adaptive denormalization
Contrastive unpaired translation
Self-supervised crack segmentation
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
Crop-paste and diffusion-based semi-supervised segmentation network for metal defect detection基于作物粘贴和扩散的半监督金属缺陷检测分割网络
Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V
Self-supervised anomaly detection in computer vision and beyond: A survey and outlook计算机视觉及以后的自监督异常检测: 综述和展望
NEURAL NETWORKS
IF6.3
DPNet: A dual prototype few-shot semantic segmentation network for crack detectionDPNet:一种用于裂缝检测的双原型少样本语义分割网络
DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
NEUROCOMPUTING
IF6.5

