Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning

Increasing the robustness of material-specific deep learning models for crack detection across different materials

(2020) Mohamad Alipour et al.   ENGINEERING STRUCTURES

Automatic Tunnel Crack Detection Based on U-Net and a Convolutional Neural Network with Alternately Updated Clique

(2020) Gang Li et al.   SENSORS

Crack Detection and Segmentation Using Deep Learning with 3D Reality Mesh Model for Quantitative Assessment and Integrated Visualization

(2020) Rony Kalfarisi et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection

(2020) Qiaoning Yang et al.   AUTOMATION IN CONSTRUCTION

MaDnet: multi-task semantic segmentation of multiple types of structural materials and damage in images of civil infrastructure

(2020) Vedhus Hoskere et al.   Journal of Civil Structural Health Monitoring

Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning

(2020) Dongho Kang et al.   AUTOMATION IN CONSTRUCTION

Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network

(2019) Shengyuan Li et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

(2019) Billie F. Spencer et al.   Engineering

Encoder-decoder network for pixel-level road crack detection in black-box images

(2019) Seongdeok Bang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Segmentation-based deep-learning approach for surface-defect detection

(2019) Domen Tabernik et al.   JOURNAL OF INTELLIGENT MANUFACTURING

DeepCrack: A deep hierarchical feature learning architecture for crack segmentation

(2019) Yahui Liu et al.   NEUROCOMPUTING

Automatic damage detection of historic masonry buildings based on mobile deep learning

(2019) Niannian Wang et al.   AUTOMATION IN CONSTRUCTION

Concrete Cracks Detection Based on FCN with Dilated Convolution

(2019) Jianming Zhang et al.   Applied Sciences-Basel

Automatic Bridge Crack Detection Using a Convolutional Neural Network

(2019) Hongyan Xu et al.   Applied Sciences-Basel

Computer vision-based concrete crack detection using U-net fully convolutional networks

(2019) Zhenqing Liu et al.   AUTOMATION IN CONSTRUCTION

Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

(2019) Chuncheng Feng et al.   KSCE Journal of Civil Engineering

Automated defect detection and classification in ashlar masonry walls using machine learning

(2019) Enrique Valero et al.   AUTOMATION IN CONSTRUCTION

Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks

(2019) Mohamad Alipour et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Deep-learning-based crack detection with applications for the structural health monitoring of gas turbines

(2019) Mahtab Mohtasham Khani et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Object Detection With Deep Learning: A Review

(2019) Zhong-Qiu Zhao et al.   IEEE Transactions on Neural Networks and Learning Systems

Densely connected deep neural network considering connectivity of pixels for automatic crack detection

(2019) Qipei Mei et al.   AUTOMATION IN CONSTRUCTION

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

(2019) Fan Yang et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

SDDNet: Real-Time Crack Segmentation

(2019) Wooram Choi et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep Transfer Learning for Image-Based Structural Damage Recognition

(2018) Yuqing Gao et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images

(2018) Hiroya Maeda et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Deep Learning–Based Fully Automated Pavement Crack Detection on 3D Asphalt Surfaces with an Improved CrackNet

(2018) Allen Zhang et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Application of Crack Identification Techniques for an Aging Concrete Bridge Inspection Using an Unmanned Aerial Vehicle

(2018) In-Ho Kim et al.   SENSORS

Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network

(2018) Xincong Yang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

(2018) Sattar Dorafshan et al.   CONSTRUCTION AND BUILDING MATERIALS

Focal loss for dense object detection

(2018) Tsung-Yi Lin et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Pixel-Wise Crack Detection Using Deep Local Pattern Predictor for Robot Application

(2018) Yundong Li et al.   SENSORS

Pixel-level crack delineation in images with convolutional feature fusion

(2018) FuTao Ni et al.   Structural Control & Health Monitoring

DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

(2018) Qin Zou et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Autonomous concrete crack detection using deep fully convolutional neural network

(2018) Cao Vu Dung et al.   AUTOMATION IN CONSTRUCTION

Automatic Road Crack Detection Using Random Structured Forests

(2016) Yong Shi et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Reliability of Crack Detection Methods for Baseline Condition Assessments

(2010) Debra F. Laefer et al.   Journal of Infrastructure Systems