Results 1 to 10 of about 592,196 (331)

Pavement Distress Estimation via Signal on Graph Processing [PDF]

Sensors, 2022
A comprehensive representation of the road pavement state of health is of great interest. In recent years, automated data collection and processing technology has been used for pavement inspection. In this paper, a new signal on graph (SoG) model of road
Salvatore Bruno, Stefania Colonnese, Gaetano Scarano, Giulia Del Serrone, Giuseppe Loprencipe   +4 more
doaj   +5 more sources

ROADS-Rover for Bituminous Pavement Distress Survey: An Unmanned Ground Vehicle (UGV) Prototype for Pavement Distress Evaluation. [PDF]

Sensors (Basel), 2022
Maintenance has a major impact on the financial plan of road managers. To ameliorate road conditions and reduce safety constraints, distress evaluation methods should be efficient and should avoid being time consuming. That is why road cadastral catalogs should be updated periodically, and interventions should be provided for specific management plans.
Mei A, Zampetti E, Di Mascio P, Fontinovo G, Papa P, D'Andrea A.   +5 more
europepmc   +5 more sources

Pavement Distress Detection Methods: A Review [PDF]

Infrastructures, 2018
The road pavement conditions affect safety and comfort, traffic and travel times, vehicles operating cost, and emission levels. In order to optimize the road pavement management and guarantee satisfactory mobility conditions for all road users, the ...
Antonella Ragnoli, Maria Rosaria De Blasiis, Alessandro Di Benedetto   +2 more
doaj   +6 more sources

UAV-PDD2023: A benchmark dataset for pavement distress detection based on UAV images. [PDF]

Data 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.
Yan H, Zhang J.
europepmc   +2 more sources

Attain: Inclusive annotated pavement distress types and severity datasetMendeley Data [PDF]

Data in Brief
Pavement distress detection plays a crucial role in pavement management and rehabilitation (M&R) by providing essential data for maintenance decision-making.
Mohammad Rezaeimanesh, Amir Golroo, Mohammad Sadegh Fahmani, Mohammad Javad Amani, Farid Hasanitabaar, Mohammad Saleh Entezari, Sane Karimi   +6 more
doaj   +2 more sources

ISTD-PDS7: A Benchmark Dataset for Multi-Type Pavement Distress Segmentation from CCD Images in Complex Scenarios

Remote Sensing, 2023
The lack of large-scale, multi-scene, and multi-type pavement distress training data reduces the generalization ability of deep learning models in complex scenes, and limits the development of pavement distress extraction algorithms.
Weidong Song, Zaiyan Zhang, Bing Zhang, Guohui Jia, Hongbo Zhu, Jinhe Zhang   +5 more
doaj   +2 more sources

LTPLN: Automatic pavement distress detection. [PDF]

PLoS One
Automatic 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.
Huang WQ, Feng L, He YL.
europepmc   +3 more sources

A Large-Scale Image Repository for Automated Pavement Distress Analysis and Degradation Trend Prediction [PDF]

Scientific Data
In recent years, automated detection technologies for large-scale pavement distress have become a focal point of research in the transportation sector.
Hanlin Yang, Jinpu Cao, Jun Wan, Qian Gao, Chenglong Liu, Martin Fischer, Yuchuan Du, Yishun Li, Pooja Jain, Difei Wu   +9 more
doaj   +2 more sources

Pavement Distress Initiation Prediction by Time-Lag Analysis and Logistic Regression

Applied Sciences, 2022
Pavement condition prediction plays a vital role in pavement maintenance. Many prediction models and analyses have been conducted based on long-term pavement condition data.
Hao Liu, Yishun Li, Chenglong Liu, Guohong Shen, Hui Xiang   +4 more
doaj   +2 more sources

Automated Multi-Type Pavement Distress Segmentation and Quantification Using Transformer Networks for Pavement Condition Index Prediction

Applied Sciences
Pavement distress detection is a crucial task when assessing pavement performance conditions. Here, a novel deep-learning method based on a transformer network, referred to as ISTD-DisNet, is proposed for multi-type pavement distress semantic ...
Zaiyan Zhang, Weidong Song, Yangyang Zhuang, Bing Zhang, Jiachen Wu   +4 more
doaj   +2 more sources