Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review

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Human-level control through deep reinforcement learning

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Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks

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Deep learning and its applications to machine health monitoring

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Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types

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Vibration Based Condition Monitoring: A Review

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A Survey on Deep Learning

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A review of structural health monitoring literature 1996-2001

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Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

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Autonomous concrete crack detection using deep fully convolutional neural network

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

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Emerging Artificial Intelligence Methods in Structural Engineering

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Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection

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Automated Pixel‐Level Pavement Crack Detection on 3D Asphalt Surfaces Using a Deep‐Learning Network

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Crack detection using image processing: A critical review and analysis

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NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

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

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

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Deep Transfer Learning for Image‐Based Structural Damage Recognition

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Rethinking the Inception Architecture for Computer Vision

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Structural Damage Detection with Automatic Feature‐Extraction through Deep Learning

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Computer vision and deep learning–based data anomaly detection method for structural health monitoring

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Vision‐Based Automated Crack Detection for Bridge Inspection

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1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

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The State of the Art of Data Science and Engineering in Structural Health Monitoring

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Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring

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

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Autonomous UAVs for Structural Health Monitoring Using Deep Learning and an Ultrasonic Beacon System with Geo‐Tagging

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Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization

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Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection

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Benchmarking State-of-the-Art Deep Learning Software Tools

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Recent progress and future trends on damage identification methods for bridge structures

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Vision-based detection of loosened bolts using the Hough transform and support vector machines

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Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning

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A novel deep learning-based method for damage identification of smart building structures

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Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

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

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Automated Pixel-Level Pavement Crack Detection on 3D Asphalt Surfaces with a Recurrent Neural Network

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Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images

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

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

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Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks

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Supervised Deep Restricted Boltzmann Machine for Estimation of Concrete

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Performance Comparison of Pretrained Convolutional Neural Networks on Crack Detection in Buildings

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Image‐Based Crack Detection for Real Concrete Surfaces

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A deep-learning-based approach for fast and robust steel surface defects classification

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Vision-based multipoint displacement measurement for structural health monitoring

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Deep Learning for Detecting Building Defects Using Convolutional Neural Networks

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Structural Displacement Measurement Using an Unmanned Aerial System

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Concrete Cracks Detection Based on Deep Learning Image Classification

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Road Damage Detection Using Deep Neural Networks with Images Captured Through a SmartphonePreprint

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Automatic classification of pavement crack using deep convolutional neural network

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A vision-based method for crack detection in gusset plate welded joints of steel bridges using deep convolutional neural networks

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Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks

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Unified Approach to Pavement Crack and Sealed Crack Detection Using Preclassification Based on Transfer Learning

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Deep Convolutional Neural Network for Structural Dynamic Response Estimation and System Identification

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Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural NetworkPreprint

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Image‐Based Concrete Crack Detection Using Convolutional Neural Network and Exhaustive Search Technique

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Comparative analysis of image binarization methods for crack identification in concrete structures

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Vibration‐based structural condition assessment using convolution neural networks

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Structural health monitoring using extremely compressed data through deep learning

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Deep learning-based automatic volumetric damage quantification using depth camera

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Concrete crack detection using context-aware deep semantic segmentation network

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Quasi-autonomous bolt-loosening detection method using vision-based deep learning and image processing

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Automatic seismic damage identification of reinforced concrete columns from images by a region-based deep convolutional neural network

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Bridge inspection: human performance, unmanned aerial systems and automation

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Deep learning–based autonomous concrete crack evaluation through hybrid image scanning

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

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Multimedia Big Data Analytics

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A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures

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Autonomous bolt loosening detection using deep learning

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Lost data recovery for structural health monitoring based on convolutional neural networks

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Convolutional neural networks for automated damage recognition and damage type identification

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Fully automated vision-based loosened bolt detection using the Viola–Jones algorithm

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Single-Sensor Acoustic Emission Source Localization in Plate-Like Structures Using Deep Learning

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The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

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