相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Image-based concrete crack detection in tunnels using deep fully convolutional networks
Yupeng Ren et al.
CONSTRUCTION AND BUILDING MATERIALS (2020)
Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection
Fan Yang et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)
A vision-based active learning convolutional neural network model for concrete surface crack detection
Zhen Wang et al.
ADVANCES IN STRUCTURAL ENGINEERING (2020)
SDDNet: Real-Time Crack Segmentation
Wooram Choi et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)
Autonomous concrete crack detection using deep fully convolutional neural network
Cao Vu Dung et al.
AUTOMATION IN CONSTRUCTION (2019)
Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring
Billie F. Spencer et al.
ENGINEERING (2019)
Structural crack detection using deep learning-based fully convolutional networks
Xiao-Wei Ye et al.
ADVANCES IN STRUCTURAL ENGINEERING (2019)
SigUNet: signal peptide recognition based on semantic segmentation
Jhe-Ming Wu et al.
BMC BIOINFORMATICS (2019)
Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network
Nhat-Duc Hoang et al.
AUTOMATION IN CONSTRUCTION (2018)
A method of detecting the cracks of concrete undergo high-temperature
Lang Li et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naive Bayes Data Fusion
Fu-Chen Chen et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
Deep learning based image recognition for crack and leakage defects of metro shield tunnel
Hong-wei Huang et al.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2018)
Automatic Pixel-Level Pavement Crack Detection Using Information of Multi-Scale Neighborhoods
Dihao Ai et al.
IEEE ACCESS (2018)
Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
Sattar Dorafshan et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
Osama Abdeljaber et al.
JOURNAL OF SOUND AND VIBRATION (2017)
Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
Image analysis for detection of bugholes on concrete surface
Baoju Liu et al.
CONSTRUCTION AND BUILDING MATERIALS (2017)
Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection
Rabih Amhaz et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2016)
Automatic Road Crack Detection Using Random Structured Forests
Yong Shi et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2016)
A new computational approach to cracks quantification from 2D image analysis: Application to micro-cracks description in rocks
Alessio Arena et al.
COMPUTERS & GEOSCIENCES (2014)
Crack Tree: Automatic crack detection from pavement images
Qin Zou et al.
PATTERN RECOGNITION LETTERS (2012)
Fast crack detection method for large-size concrete surface images using percolation-based image processing
Tomoyuki Yamaguchi et al.
MACHINE VISION AND APPLICATIONS (2010)