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Deep Learning in Data-Driven Pavement Image Analysis and Automated Distress Detection: A Review
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure
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Recognition, location, measurement, and 3D reconstruction of concealed cracks using convolutional neural networks
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Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection
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Mitigation strategies for reflection cracking in rehabilitated pavements – A synthesis
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An efficient and reliable coarse-to-fine approach for asphalt pavement crack detection
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Network level pavement evaluation with 1 mm 3D survey system
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A survey on deep learning in medical image analysis
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A systematic study of the class imbalance problem in convolutional neural networks
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CrackTree: Automatic crack detection from pavement images
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Unified Approach to Pavement Crack and Sealed Crack Detection Using Preclassification Based on Transfer Learning
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Critical Assessment of Pavement Distress Segmentation Methods
inferredcites →https://doi.org/10.1061/9780784480823.036openalex-snapshot
Deep Active Learning for Civil Infrastructure Defect Detection and Classification
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Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science
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Performance comparison of deep learning frameworks in image classification problems using convolutional and recurrent networks
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Automation of Pavement Surface Crack Detection using the Continuous Wavelet Transform
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CrackIT — An image processing toolbox for crack detection and characterization
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Road crack detection using deep convolutional neural network
inferredcites →https://doi.org/10.1109/ictis.2017.8047878openalex-snapshot
Grid-based pavement crack analysis using deep learning
inferredcites →https://doi.org/10.1109/ijcnn.2017.7966101openalex-snapshot
How to get pavement distress detection ready for deep learning? A systematic approach
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Chest pathology detection using deep learning with non-medical training
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Automatic Road Crack Detection and Characterization
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Automatic Road Crack Detection Using Random Structured Forests
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Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
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Beamlet Transform‐Based Technique for Pavement Crack Detection and Classification
inferredcites →https://doi.org/10.1111/mice.12263openalex-snapshot
Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks
inferredcites →https://doi.org/10.1111/mice.12297openalex-snapshot
Automated Pixel‐Level Pavement Crack Detection on 3D Asphalt Surfaces Using a Deep‐Learning Network
inferredcites →https://doi.org/10.1117/12.2264075openalex-snapshot
A method based on machine learning using hand-crafted features for crack detection from asphalt pavement surface images
inferredcites →https://doi.org/10.1117/12.2266911openalex-snapshot
Development of a classification method for a crack on a pavement surface images using machine learning
inferredcites →https://doi.org/10.1155/2008/861701openalex-snapshot
Evaluating Pavement Cracks with Bidimensional Empirical Mode Decomposition
inferredcites →https://doi.org/10.1155/2011/989354openalex-snapshot
Automatic Road Pavement Assessment with Image Processing: Review and Comparison
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Deep Learning in Visual Computing and Signal Processing
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Quality Management of Pavement Condition Data Collection
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Deeper Networks for Pavement Crack Detection
inferredcites →https://doi.org/10.3141/2024-09openalex-snapshot
Wavelet-Based Pavement Distress Image Edge Detection with À Trous Algorithm
inferredcites →https://doi.org/10.4018/978-1-4666-9700-3openalex-snapshot
Advanced Pavement Health Monitoring and Management
inferredcites →https://doi.org/10.48550/arxiv.1408.5093openalex-snapshot
Caffe: Convolutional Architecture for Fast Feature Embedding
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Large-scale Continual Road Inspection: Visual Infrastructure Assessment in the Wild
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CRACK DAMAGE DETECTION IN UNMANNED AERIAL VEHICLE IMAGES OF CIVIL INFRASTRUCTURE USING PRE-TRAINED DEEP LEARNING MODEL
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Research on Urban Road Pavement Distress Detection System Based on Improved YOLOv4
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English Oral Automatic Translation System Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/icmi60790.2024.10586098openalex-snapshot
Automated Pavement Cracks Detection and Classification Using Deep Learning
inferred← citeshttps://doi.org/10.1109/icsp62122.2024.10743402openalex-snapshot
Road Distress Identification Using GPR Signals and U-Net Model
inferred← citeshttps://doi.org/10.1109/ijcnn.2019.8852257openalex-snapshot
Improving Visual Road Condition Assessment by Extensive Experiments on the Extended GAPs Dataset
inferred← citeshttps://doi.org/10.1109/inmic60434.2023.10465839openalex-snapshot
Motorbike Driving Activity Recognition Using Smartphone Motion Sensors
inferred← citeshttps://doi.org/10.1109/jiot.2020.3024885openalex-snapshot
EcRD: Edge-Cloud Computing Framework for Smart Road Damage Detection and Warning
inferred← citeshttps://doi.org/10.1109/raai56146.2022.10092963openalex-snapshot
Proof of Concept Design for Terrain Type Recognition in Urban Environments
inferred← citeshttps://doi.org/10.1109/sas58821.2023.10254080openalex-snapshot
A Robust and Real-Time Hyper-Spectral Sensor-Fusion Model for Concrete Crack Segmentation
inferred← citeshttps://doi.org/10.1109/smap59435.2023.10255205openalex-snapshot
Safe vs Unsafe Crosswalks: Assessing the Factors Related to Pedestrian Safety
inferred← citeshttps://doi.org/10.1109/tase.2024.3379945openalex-snapshot
Promoting Automatic Detection of Road Damage: A High-Resolution Dataset, a New Approach, and a New Evaluation Criterion
inferred← citeshttps://doi.org/10.1109/tim.2023.3324689openalex-snapshot
An Image-Based Hairline Crack Identification Method for Metal Parts
inferred← citeshttps://doi.org/10.1109/tits.2024.3360263openalex-snapshot
Robust Semantic Segmentation for Automatic Crack Detection Within Pavement Images Using Multi-Mixing of Global Context and Local Image Features
inferred← citeshttps://doi.org/10.1109/tla.2019.9011537openalex-snapshot
Deep Learning: Current State
inferred← citeshttps://doi.org/10.1109/tsmc.2022.3227209openalex-snapshot
Cognitive-Based Crack Detection for Road Maintenance: An Integrated System in Cyber-Physical-Social Systems
inferred← citeshttps://doi.org/10.1109/tsp49548.2020.9163538openalex-snapshot
A Two-Stream Context-Aware ConvNet for Pavement Distress Detection
inferred← citeshttps://doi.org/10.1111/exsy.13784openalex-snapshot
Intelligent Crack Detection in Infrastructure Using Computer Vision at the Edge
inferred← citeshttps://doi.org/10.1111/mice.12674openalex-snapshot
Cross‐scene pavement distress detection by a novel transfer learning framework
inferred← citeshttps://doi.org/10.1111/mice.12947openalex-snapshot
Spatiotemporal matching method for tracking pavement distress using high‐frequency detection data
inferred← citeshttps://doi.org/10.1117/12.3033782openalex-snapshot
AI-based recognition for road distressed from GPR measurement using artificial neural networks
inferred← citeshttps://doi.org/10.1139/cjce-2020-0246openalex-snapshot
Crack grid detection and calculation based on convolutional neural network
inferred← citeshttps://doi.org/10.1145/3511176.3511195openalex-snapshot
Robust Deep Representation Learning for Road Crack Detection
inferred← citeshttps://doi.org/10.1145/3523111.3523113openalex-snapshot
A Semantic Segmentation Approach for Road Defect Detection and Quantification
inferred← citeshttps://doi.org/10.1145/3656766.3656970openalex-snapshot
A Detection and Classification Method of Asphalt Pavement Crack based on Vision Transformer
inferred← citeshttps://doi.org/10.1155/2019/2470735openalex-snapshot
Real‐Time Road Crack Mapping Using an Optimized Convolutional Neural Network
inferred← citeshttps://doi.org/10.1155/2020/2513147openalex-snapshot
SBS Content Detection for Modified Asphalt Using Deep Neural Network
inferred← citeshttps://doi.org/10.1155/2020/5804835openalex-snapshot
Dynamic Pavement Distress Image Stitching Based on Fine-Grained Feature Matching
inferred← citeshttps://doi.org/10.1155/2022/4684669openalex-snapshot
Improvement of Multiclass Classification of Pavement Objects Using Intensity and Range Images
inferred← citeshttps://doi.org/10.1177/0361198120907283openalex-snapshot
Pavement Image Datasets: A New Benchmark Dataset to Classify and Densify Pavement Distresses
inferred← citeshttps://doi.org/10.1177/03611981221127273openalex-snapshot
Comparing Different Deep Learning Architectures as Vision-Based Multi-Label Classifiers for Identification of Multiple Distresses on Asphalt Pavement
inferred← citeshttps://doi.org/10.1177/03611981241239958openalex-snapshot
Hybrid Transfer Learning and Support Vector Machine Models for Asphalt Pavement Distress Classification
inferred← citeshttps://doi.org/10.1177/03611981261424238openalex-snapshot
Determination of Pavement Distress Severity Using Machine Learning: Systematic Review
inferred← citeshttps://doi.org/10.1186/s43065-026-00178-yopenalex-snapshot
Application of artificial intelligence methods in the international roughness index prediction of rigid and composite pavements: a systematic review
inferred← citeshttps://doi.org/10.1680/jmuen.21.00037openalex-snapshot
Assessment of the resilience of pedestrian roads based on image deep learning models
inferred← citeshttps://doi.org/10.20517/jsegc.2021.09openalex-snapshot
Moving towards smart transportation with machine learning and Internet of Things (IoT): a review
inferred← citeshttps://doi.org/10.20868/ade.2024.5487openalex-snapshot
Use of unmanned aerial vehicles in the determination of pavement surface condition indices
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8892244/v1openalex-snapshot
Deep neural network with local-global context-aware feature fusion for crack detection
inferred← citeshttps://doi.org/10.2139/ssrn.4982476openalex-snapshot
A Pavement Distress Detection And Severity Analysis
inferred← citeshttps://doi.org/10.2139/ssrn.5273133openalex-snapshot
Vision Transformer-Based Road Condition Classification Using Optimized Xgboost for Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.2139/ssrn.7031723openalex-snapshot
Low-Cost Pavement Distress Detection and Mapping Using Smartphone Imagery and Data-Efficient DDPM Augmentation with YOLOv8
inferred← citeshttps://doi.org/10.23919/ien.2022.0040openalex-snapshot
Shaping future low-carbon energy and transportation systems: Digital technologies and applications
inferred← citeshttps://doi.org/10.24054/rcta.v2i42.2597openalex-snapshot
DEEP NEURAL NETWORKS FOR SENSITIVITY ASSESSMENT OF DESIGN VARIABLES ON THE STRUCTURAL DESIGN PARAMETERS OF FLEXIBLE PAVEMENTS FOR LOW-TRAFFIC VOLUME ROADS
inferred← citeshttps://doi.org/10.24423/cames.267openalex-snapshot
A comparison of deep convolutional neural networks for image-based detection of concrete surface cracks
inferred← citeshttps://doi.org/10.31390/gradschool_dissertations.5270openalex-snapshot
Identification of Top-down, Bottom-up, and Cement-Treated Reflective Cracks Using Convolutional Neural Network and Artificial Neural Network
inferred← citeshttps://doi.org/10.3233/scs-230001openalex-snapshot
A review on computer vision and machine learning techniques for automated road surface defect and distress detection
inferred← citeshttps://doi.org/10.32469/10355/85799openalex-snapshot
Developing a modern recycled mix design and automatic pavement monitoring system
inferred← citeshttps://doi.org/10.32604/cmc.2023.042183openalex-snapshot
Automated Pavement Crack Detection Using Deep Feature Selection and Whale Optimization Algorithm
inferred← citeshttps://doi.org/10.32604/cmc.2024.057213openalex-snapshot
A Hybrid Approach for Pavement Crack Detection Using Mask R-CNN and Vision Transformer Model
inferred← citeshttps://doi.org/10.33411/ijist/565openalex-snapshot
Contemporary Study of Machine Learning Algorithms for Traffic Density Estimation in Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.3390/app10010319openalex-snapshot
Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
inferred← citeshttps://doi.org/10.3390/app11094269openalex-snapshot
CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots
inferred← citeshttps://doi.org/10.3390/app12031374openalex-snapshot
A Comprehensive Review of Deep Learning-Based Crack Detection Approaches
inferred← citeshttps://doi.org/10.3390/app14114817openalex-snapshot
How to Make a State of the Art Report—Case Study—Image-Based Road Crack Detection: A Scientometric Literature Review
inferred← citeshttps://doi.org/10.3390/app14156640openalex-snapshot
Sustainable Pavement Management: Harnessing Advanced Machine Learning for Enhanced Road Maintenance
inferred← citeshttps://doi.org/10.3390/app9132686openalex-snapshot
Concrete Cracks Detection Based on FCN with Dilated Convolution
inferred← citeshttps://doi.org/10.3390/drones8060244openalex-snapshot
Automatic Road Pavement Distress Recognition Using Deep Learning Networks from Unmanned Aerial Imagery
inferred← citeshttps://doi.org/10.3390/electronics12010088openalex-snapshot
Architectural Threats to Security and Privacy: A Challenge for Internet of Things (IoT) Applications
inferred← citeshttps://doi.org/10.3390/electronics13020312openalex-snapshot
CrackYOLO: Rural Pavement Distress Detection Model with Complex Scenarios
inferred← citeshttps://doi.org/10.3390/fi11040094openalex-snapshot
A Review of Machine Learning and IoT in Smart Transportation
inferred← citeshttps://doi.org/10.3390/info11120568openalex-snapshot
Using UAV Based 3D Modelling to Provide Smart Monitoring of Road Pavement Conditions
inferred← citeshttps://doi.org/10.3390/infrastructures10030064openalex-snapshot
Review and Insights Toward Cognitive Digital Twins in Pavement Assets for Construction 5.0
inferred← citeshttps://doi.org/10.3390/infrastructures10090248openalex-snapshot
Evaluation of Connected Vehicle Pavement Roughness Data for Statewide Needs Assessment
inferred← citeshttps://doi.org/10.3390/infrastructures11080276openalex-snapshot
Analyzing Interrelationships Between Asphalt Pavement Distresses Across Multiple Lebanese Regions Using Association Rule Mining for Enhanced Maintenance Strategies
inferred← citeshttps://doi.org/10.3390/infrastructures7090113openalex-snapshot
Development of a Cognitive Digital Twin for Pavement Infrastructure Health Monitoring
inferred← citeshttps://doi.org/10.3390/infrastructures8120170openalex-snapshot
Machine Learning for Prediction of the International Roughness Index on Flexible Pavements: A Review, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.3390/infrastructures9120213openalex-snapshot
Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions
inferred← citeshttps://doi.org/10.3390/rs15092400openalex-snapshot
Image Processing Techniques for Concrete Crack Detection: A Scientometrics Literature Review
inferred← citeshttps://doi.org/10.3390/s20092557openalex-snapshot
Improved Pixel-Level Pavement-Defect Segmentation Using a Deep Autoencoder
inferred← citeshttps://doi.org/10.3390/s21155137openalex-snapshot
Attention-Based Multi-Scale Convolutional Neural Network (A+MCNN) for Multi-Class Classification in Road Images
inferred← citeshttps://doi.org/10.3390/s24206757openalex-snapshot
Research on Road Internal Disease Identification Algorithm Based on Attention Fusion Mechanisms
inferred← citeshttps://doi.org/10.3390/s25103091openalex-snapshot
Exploring the Effectiveness of Road Maintenance Interventions on IRI Value Using Crowdsourced Connected Vehicle Data
inferred← citeshttps://doi.org/10.3390/su11041077openalex-snapshot
Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018
inferred← citeshttps://doi.org/10.3390/su142114304openalex-snapshot
Data Augmentation by an Additional Self-Supervised CycleGAN-Based for Shadowed Pavement Detection
inferred← citeshttps://doi.org/10.3390/sym11040496openalex-snapshot
An Automated Training of Deep Learning Networks by 3D Virtual Models for Object Recognition
inferred← citeshttps://doi.org/10.3390/sym17111992openalex-snapshot
A Review of Pavement Performance Deterioration Modeling: Influencing Factors and Techniques
inferred← citeshttps://doi.org/10.35940/ijeat.a4273.13030224openalex-snapshot
Airport Runway Crack Detection to Classify and Densify Surface Crack Type
inferred← citeshttps://doi.org/10.4018/978-1-6684-4045-2.ch006openalex-snapshot
Machine Learning for Internet of Things-Based Smart Transportation Networks
inferred← citeshttps://doi.org/10.47839/ijc.20.3.2288openalex-snapshot
Comparison of Semantic Convolution Neural Networks on the Example of Crack Segmentation in Asphalt Images
inferred← citeshttps://doi.org/10.48175/ijarsct-3526openalex-snapshot
Smart Road Damage Detection and Warning using Machine Learning
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