CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV Inspections
Author:
Affiliation:
1. Lehigh University,P.C. Rossin College of Engineering and Applied Science,Department of Computer Science and Engineering,Bethlehem,PA,USA,18015
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10609961/10609862/10611660.pdf?arnumber=10611660
Reference59 articles.
1. CycleADC-Net: A crack segmentation method based on multi-scale feature fusion
2. SDDNet: Real-Time Crack Segmentation
3. DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
4. Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning
5. Automated pavement crack detection and segmentation based on two‐step convolutional neural network
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