LTPLN: Automatic pavement distress detection [PDF]
PLOS ONEAutomatic pavement disease detection aims to address the inefficiency in practical detection. However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios.
Wen-Qing Huang, Liu Feng, Yuan-Lie He
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UAV-PDD2023: A benchmark dataset for pavement distress detection based on UAV images [PDF]
Data in Brief, 2023 The UAV-PDD2023 dataset consists of pavement distress images captured by unmanned aerial vehicles (UAVs) in China with more than 11,150 instances under two different weather conditions and across varying levels of construction quality.
Haohui Yan, Junfei Zhang
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LRD-DETR: A Lightweight RT-DETR-Based Model for Road Distress Detection [PDF]
SensorsIntelligent road distress detection technology has emerged as an important research topic in the field of highway maintenance. However, the accuracy and practicality of pavement distress detection are constrained by multiple factors, primarily including ...
Chen Dong, Yunwei Zhang
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Attain: Inclusive annotated pavement distress types and severity datasetMendeley Data [PDF]
Data in BriefPavement distress detection plays a crucial role in pavement management and rehabilitation (M&R) by providing essential data for maintenance decision-making.
Mohammad Rezaeimanesh +6 more
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A Large-Scale Image Repository for Automated Pavement Distress Analysis and Degradation Trend Prediction [PDF]
Scientific DataIn recent years, automated detection technologies for large-scale pavement distress have become a focal point of research in the transportation sector.
Hanlin Yang +9 more
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PaveDistress: A comprehensive dataset of pavement distresses detection [PDF]
Data in BriefThe PaveDistress dataset contains high-resolution images of road surface distresses, including cracks, repairs, potholes, and background images without defects. The data were collected using a specialized pavement inspection vehicle along the S315 highway in China.
Zhen Liu +3 more
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Onboard LiDAR–Camera Deployment Optimization for Pavement Marking Distress Fusion Detection [PDF]
SensorsPavement markings, as a crucial component of traffic guidance and safety facilities, are subject to degradation and abrasion after a period of service.
Ciyun Lin +4 more
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Applying a Combination of the YOLOv8 Model and 3D Point Cloud Images in Asphalt Pavement Maintenance [PDF]
SensorsAsphalt pavement distress detection plays a pivotal role in highway maintenance, providing an essential basis for optimizing maintenance strategies and allocating funding. Consequently, quick detection and efficient identification of distress are crucial
Yangyang Wang +6 more
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Automated Pavement Distress Detection Based on Convolutional Neural Network
IEEE AccessPavement distress detection is crucial in road health assessment and monitoring. However, there are still some challenges in extracting pavement distress based on deep learning: such as insufficient segmentation, extraction errors and discontinuities. In
Jinhe Zhang +4 more
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Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images [PDF]
SensorsPavement surface distresses are analyzed by transportation agencies to determine section performance across their pavement networks. To efficiently collect and evaluate thousands of lane-miles, automated processes utilizing image-capturing techniques and
Carlos Sanchez +3 more
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