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Pavement Crack Detection Method Based on Deep Learning Models
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s00138-021-01171-zopenalex-snapshot
Automated detection and classification of spilled loads on freeways based on improved YOLO network
inferredcites →https://doi.org/10.1007/s00366-018-0611-9openalex-snapshot
A novel method for asphalt pavement crack classification based on image processing and machine learning
inferredcites →https://doi.org/10.1007/s11265-013-0813-8openalex-snapshot
An Automatic Approach for Accurate Edge Detection of Concrete Crack Utilizing 2D Geometric Features of Crack
inferredcites →https://doi.org/10.1007/s13349-020-00447-8openalex-snapshot
One stage detector (RetinaNet)-based crack detection for asphalt pavements considering pavement distresses and surface objects
inferredcites →https://doi.org/10.1016/j.image.2020.115984openalex-snapshot
Joint feature representation and classification via adaptive graph semi-supervised nonnegative matrix factorization
inferredcites →https://doi.org/10.1016/j.imavis.2011.10.003openalex-snapshot
FoSA: F* Seed-growing Approach for crack-line detection from pavement images
inferredcites →https://doi.org/10.1016/j.measurement.2020.108693openalex-snapshot
Automatic recognition and analysis system of asphalt pavement cracks using interleaved low-rank group convolution hybrid deep network and SegNet fusing dense condition random field
inferredcites →https://doi.org/10.1016/j.measurement.2020.108698openalex-snapshot
RENet: Rectangular convolution pyramid and edge enhancement network for salient object detection of pavement cracks
inferredcites →https://doi.org/10.1016/j.patcog.2019.03.024openalex-snapshot
Joint graph optimization and projection learning for dimensionality reduction
inferredcites →https://doi.org/10.1049/iet-ipr.2019.0973openalex-snapshot
Pavement crack detection network based on pyramid structure and attention mechanism
inferredcites →https://doi.org/10.1109/access.2019.2961375openalex-snapshot
Improving the Efficiency of Encoder-Decoder Architecture for Pixel-Level Crack Detection
inferredcites →https://doi.org/10.1109/access.2021.3050401openalex-snapshot
Pavement Crack Detection Algorithm Based on Densely Connected and Deeply Supervised Network
inferredcites →https://doi.org/10.1109/cisp.2008.13openalex-snapshot
Novel Approach to Pavement Image Segmentation Based on Neighboring Difference Histogram Method
inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-snapshot
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00913openalex-snapshot
Path Aggregation Network for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00075openalex-snapshot
Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00203openalex-snapshot
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
inferredcites →https://doi.org/10.1109/iccv.2019.00612openalex-snapshot
CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features
inferredcites →https://doi.org/10.1109/ictis.2017.8047878openalex-snapshot
Grid-based pavement crack analysis using deep learning
inferredcites →https://doi.org/10.1109/itaic.2014.7065001openalex-snapshot
The design of glass crack detection system based on image preprocessing technology
inferredcites →https://doi.org/10.1109/kam.2008.29openalex-snapshot
Novel Approach to Pavement Cracking Automatic Detection Based on Segment Extending
inferredcites →https://doi.org/10.1109/tcsvt.2019.2892971openalex-snapshot
Non-Negative Matrix Factorization With Locality Constrained Adaptive Graph
inferredcites →https://doi.org/10.1109/tie.2017.2764844openalex-snapshot
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion
inferredcites →https://doi.org/10.1109/tip.2018.2878966openalex-snapshot
DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
inferredcites →https://doi.org/10.1109/tits.2016.2552248openalex-snapshot
Automatic Road Crack Detection Using Random Structured Forests
inferredcites →https://doi.org/10.1109/tits.2019.2891167openalex-snapshot
Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V
inferredcites →https://doi.org/10.1109/tits.2019.2910595openalex-snapshot
Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1111/j.1467-8667.2011.00736.xopenalex-snapshot
Automatic Road Defect Detection by Textural Pattern Recognition Based on AdaBoost
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/10.1111/mice.12412openalex-snapshot
Automatic Pixel‐Level Crack Detection and Measurement Using Fully Convolutional Network
inferredcites →https://doi.org/10.3390/coatings10020152openalex-snapshot
Ensemble of Deep Convolutional Neural Networks for Automatic Pavement Crack Detection and Measurement
inferredcites →https://doi.org/10.3390/s111009628openalex-snapshot
Adaptive Road Crack Detection System by Pavement Classification
inferredcites →https://doi.org/10.3390/s18103452openalex-snapshot
Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique
inferredcites →https://doi.org/10.3390/s21030974openalex-snapshot
Autonomous Vision-Based Primary Distribution Systems Porcelain Insulators Inspection Using UAVs
inferredcites →https://doi.org/10.4103/0256-4602.62225openalex-snapshot
Automatic Pavement Crack Detection Using Texture and Shape Descriptors
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Automatic Detection of Concrete Cracks Using Self-Supervised Dinov2 Image Classification
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Few-shot crack detection based on image processing and improved YOLOv5
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Airport Pavement Distress Analysis
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A Neural Network-Based Asphalt Pavement Crack Classification Model Using Image Processing and Random Boosted Differential Flower Pollination
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Detection of Potholes in Asphalt Pavements Using YOLOv4 Architecture
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Real-Time Pavement Crack Detection for Cutting Machines: Enhancing YOLOv5 with Lightweight Modules and Attention Mechanisms
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SHAP-Driven Pavement Maintenance Prediction and Prioritization Framework Using LightGBM
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Measurement of Asphalt Pavement Crack Length Using YOLO V5-BiFPN
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inferred← citeshttps://doi.org/10.3390/buildings12122135openalex-snapshot
Wall Crack Multiclass Classification: Expertise-Based Dataset Construction and Learning Algorithms Performance Comparison
inferred← citeshttps://doi.org/10.3390/buildings16122313openalex-snapshot
Damage Attention-Aware Dense Layered Framework for Surface Crack Classification
inferred← citeshttps://doi.org/10.3390/drones7030189openalex-snapshot
Segmentation Detection Method for Complex Road Cracks Collected by UAV Based on HC-Unet++
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/electronics13224426openalex-snapshot
Mixed Reality-Based Concrete Crack Detection and Skeleton Extraction Using Deep Learning and Image Processing
inferred← citeshttps://doi.org/10.3390/electronics14204017openalex-snapshot
Research on Preventive Maintenance Technology for Highway Cracks Based on Digital Image Processing
inferred← citeshttps://doi.org/10.3390/infrastructures10120348openalex-snapshot
An Integrated Framework with SAM and OCR for Pavement Crack Quantification and Geospatial Mapping
inferred← citeshttps://doi.org/10.3390/infrastructures9020034openalex-snapshot
Asphalt Pavement Damage Detection through Deep Learning Technique and Cost-Effective Equipment: A Case Study in Urban Roads Crossed by Tramway Lines
inferred← citeshttps://doi.org/10.3390/math11102377openalex-snapshot
An Improved YOLOv5 Crack Detection Method Combined with a Bottleneck Transformer
inferred← citeshttps://doi.org/10.3390/math11153277openalex-snapshot
Research on Real-Time Detection Algorithm for Pavement Cracks Based on SparseInst-CDSM
inferred← citeshttps://doi.org/10.3390/math12050690openalex-snapshot
Auxcoformer: Auxiliary and Contrastive Transformer for Robust Crack Detection in Adverse Weather Conditions
inferred← citeshttps://doi.org/10.3390/mca30060132openalex-snapshot
Detection in Road Crack Images Based on Sparse Convolution
inferred← citeshttps://doi.org/10.3390/s22229019openalex-snapshot
An Exploration of Recent Intelligent Image Analysis Techniques for Visual Pavement Surface Condition Assessment
inferred← citeshttps://doi.org/10.3390/s23010053openalex-snapshot
RUC-Net: A Residual-Unet-Based Convolutional Neural Network for Pixel-Level Pavement Crack Segmentation
inferred← citeshttps://doi.org/10.3390/s24051647openalex-snapshot
Visual Detection of Road Cracks for Autonomous Vehicles Based on Deep Learning
inferred← citeshttps://doi.org/10.3390/s25175587openalex-snapshot
CrackNet-Weather: An Effective Pavement Crack Detection Method Under Adverse Weather Conditions
inferred← citeshttps://doi.org/10.3390/wevj15030102openalex-snapshot
BI-TST_YOLOv5: Ground Defect Recognition Algorithm Based on Improved YOLOv5 Model
inferred← citeshttps://doi.org/10.55145/ajest.2023.01.01.006openalex-snapshot
Using Image Processing for Automatic Detection of Pavement Surface Distress
inferred← citeshttps://doi.org/10.55549/epstem.1411085openalex-snapshot
The Classification of Asphalt Pavement Crack Images Based on Beamlet Transform
inferred← citeshttps://doi.org/10.62520/fujece.1583372openalex-snapshot
Transfer Learning Based Damage Detection in Public Areas
inferred← citeshttps://doi.org/10.63313/jcsft.9020openalex-snapshot
The improved model of YOLOV11 integrating Starnet
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