Results 281 to 290 of about 592,196 (331)

Deep Metric Learning-Based for Multi-Target Few-Shot Pavement Distress Classification

IEEE Transactions on Industrial Informatics, 2021
Pavement distress detection is of great significance for road maintenance and to ensure road safety. At present, detection methods based on deep learning have achieved outstanding performance in related fields.
Hongwen Dong, Kechen Song, Qi Wang, Yunhui Yan, Peng Jiang   +4 more
semanticscholar   +1 more source

Effects of autonomous vehicles on pavement distress & road safety and pavement distress optimization

2021
The commercial application of automation technology in passenger and freight transport will bring positive revolutionary changes in transportation mobility. Despite having more advantages, automation in trucking technology has some detrimental effects on the performance of asphalt pavement and highway safety.
openaire   +1 more source

Pavement distress detection and classification based on YOLO network

International Journal of Pavement Engineering, 2020
The detection and classification of pavement distress (PD) play a critical role in pavement maintenance and rehabilitation. Research on PD automation detection and measurement has been actively conducted.
Yuchuan Du, Ning Pan, Zihao Xu, F. Deng, Yu Shen, Hua Kang   +5 more
semanticscholar   +1 more source

Pavement Distresses at Intersections

1995
Asphaltic concrete pavements at intersections and their approaches, where traffic is required to stop and start, exhibit several types of distress. Among the more prominent forms of these distresses are deep rutting, pushing and shoving, and severe wash boarding.
Hunsucker, David Q., Meade, Bobby W.
openaire   +1 more source

YOLOv7-RDD: A Lightweight Efficient Pavement Distress Detection Model

IEEE transactions on intelligent transportation systems (Print)
The increases in the timeliness of maintenance and repair requirements for urban road pavements have created a demand for the timely detection of pavement distress.
Zhipeng Ning, Hui Wang, Shenglin Li, Zhoucong Xu   +3 more
semanticscholar   +1 more source

Pavement Distress Detection Using Street View Images Captured via Action Camera

IEEE transactions on intelligent transportation systems (Print)
Timely and accurately detection as well as rehabilitation of road surface defects are of utmost importance for ensuring road safety and minimizing maintenance cost.
Yuchen Liu, F. Liu, Wei Liu, Yucheng Huang   +3 more
semanticscholar   +1 more source

Spatiotemporal matching method for tracking pavement distress using high‐frequency detection data

Comput. Aided Civ. Infrastructure Eng., 2022
Various algorithms based on deep learning have achieved promising results in pavement distress detection. However, the detected distresses are not tracked throughout the life cycle.
Ning Pan, Hao Liu, Difei Wu, Chenglong Liu, Yupei Du   +4 more
semanticscholar   +1 more source

An Ensemble Learning Approach With Attention Mechanism for Detecting Pavement Distress and Disaster-Induced Road Damage

IEEE transactions on intelligent transportation systems (Print)
Road damage presents a significant risk to traffic safety, including pavement distress and disaster-induced damage. Thanks to their high efficiency, computer vision-based methods for pavement distress detection have been widely developed.
Shouxing Wang, Hongzan Jiao, Xin Su, Qiangqiang Yuan   +3 more
semanticscholar   +1 more source

Self-Supervised Adversarial Learning for Domain Adaptation of Pavement Distress Classification

IEEE transactions on intelligent transportation systems (Print)
Pavement distress classification is crucial for the maintenance of highways. Although many methods for classifying pavement distress are available, they all assume that training and testing datasets are drawn from the same distribution. When we introduce
Yanwen Wu, Mingjian Hong, Ao Li, Sheng Huang, Huijun Liu, Yongxin Ge   +5 more
semanticscholar   +1 more source

Advancing Pavement Distress Detection in Developing Countries: A Novel Deep Learning Approach with Locally-Collected Datasets

Advances in Data Science and Adaptive Analysis
Road infrastructure maintenance in developing countries faces unique challenges due to resource constraints and diverse environmental factors. This study addresses the critical need for efficient, accurate, and locally-relevant pavement distress ...
Blessing Agyei Kyem, E. Denteh, Joshua Kofi Asamoah, Kenneth A. Tutu, Armstrong Aboah   +4 more
semanticscholar   +1 more source