Related references
Note: Only part of the references are listed.Densely connected deep neural network considering connectivity of pixels for automatic crack detection
Qipei Mei et al.
AUTOMATION IN CONSTRUCTION (2020)
A Machine Learning Approach to Road Surface Anomaly Assessment Using Smartphone Sensors
Akanksh Basavaraju et al.
IEEE SENSORS JOURNAL (2020)
CrackU-net: A novel deep convolutional neural network for pixelwise pavement crack detection
Huyan Ju et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2020)
Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning
Dongho Kang et al.
AUTOMATION IN CONSTRUCTION (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)
Encoder-decoder network for pixel-level road crack detection in black-box images
Seongdeok Bang et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
A fast adaptive crack detection algorithm based on a double-edge extraction operator of FSM
Qijun Luo et al.
CONSTRUCTION AND BUILDING MATERIALS (2019)
DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
Yahui Liu et al.
NEUROCOMPUTING (2019)
Tunnel crack detection using coarse-to-fine region localization and edge detection
Ce Li et al.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2019)
Automatic Bridge Crack Detection Using a Convolutional Neural Network
Hongyan Xu et al.
APPLIED SCIENCES-BASEL (2019)
Computer vision-based concrete crack detection using U-net fully convolutional networks
Zhenqing Liu et al.
AUTOMATION IN CONSTRUCTION (2019)
Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder-Decoder Network
M. M. Manjurul Islam et al.
SENSORS (2019)
Detection of sealed and unsealed cracks with complex backgrounds using I (A) deep convolutional neural network
Ju Huyan et al.
AUTOMATION IN CONSTRUCTION (2019)
Foreground-background separation technique for crack detection
Fereshteh Nayyeri et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
Infrared Thermal Imaging-Based Crack Detection Using Deep Learning
Jun Yang et al.
IEEE ACCESS (2019)
Automatic Recognition of Highway Tunnel Defects Based on an Improved U-Net Model
Xiaokun Miao et al.
IEEE SENSORS JOURNAL (2019)
Automatic crack detection from 2D images using a crack measure-based B-spline level set model
H. N. Nguyen et al.
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING (2018)
Adaptive wavelet neural network for terrestrial laser scanner-based crack detection
Yelda Turkan et al.
AUTOMATION IN CONSTRUCTION (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)
A novel automatic dam crack detection algorithm based on local-global clustering
Xinnan Fan et al.
MULTIMEDIA TOOLS AND APPLICATIONS (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)
Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique
Byunghyun Kim et al.
SENSORS (2018)
Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)
SDNET2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks
Sattar Dorafshan et al.
DATA IN BRIEF (2018)
Monitoring of Corrosion-Induced Degradation in Prestressed Concrete Structure Using Embedded Piezoceramic-Based Transducers
Tianyong Jiang et al.
IEEE SENSORS JOURNAL (2017)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
An efficient and reliable coarse-to-fine approach for asphalt pavement crack detection
Dejin Zhang et al.
IMAGE AND VISION COMPUTING (2017)
Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection
Kasthurirangan Gopalakrishnan et al.
CONSTRUCTION AND BUILDING MATERIALS (2017)
Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
Supervised Deep Restricted Boltzmann Machine for Estimation of Concrete
Mohammad Hossein Rafiei et al.
ACI MATERIALS JOURNAL (2017)
Inexpensive Multimodal Sensor Fusion System for Autonomous Data Acquisition of Road Surface Conditions
Yulu Luke Chen et al.
IEEE SENSORS JOURNAL (2016)
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)
The algorithm of accelerated cracks detection and extracting skeleton by direction chain code in concrete surface image
Z. Qu et al.
IMAGING SCIENCE JOURNAL (2016)
Wireless Multimedia Sensor Network Based Subway Tunnel Crack Detection Method
Bo Shen et al.
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS (2015)
Automatic Road Pavement Assessment with Image Processing: Review and Comparison
Sylvie Chambon et al.
INTERNATIONAL JOURNAL OF GEOPHYSICS (2011)
Share Paper
