全部文献期刊会议图书|学者科研项目
中外文文献  中文文献  外文文献
作者:Lu Sun , Zedong Qian
来源:[J].Measurement(IF 1.13), 2016, Vol.86, pp.26-40
摘要:Abstract(#br)Non-uniform background of pavement images results in difficulties when segmenting pavement images for pavement distress identification. A novel and fast non-uniform background removal algorithm based on multi-scale wavelet transform is presented. The algorithm uses m...
作者:Fereidoon Moghadas Nejad , Hamzeh Zakeri
来源:[J].Expert Systems With Applications(IF 1.854), 2010, Vol.38 (3), pp.2857-2872
摘要:Abstract(#br)The research presented in this article is aimed at the development of an automated imaging system for distress detection and isolation in asphalt pavement distress obtained from pavement image acquisition system (PIAS). This article focuses on comparing the discrimi...
作者:Fereidoon Moghadas Nejad , Hamzeh Zakeri
来源:[J].Expert Systems With Applications(IF 1.854), 2011, Vol.38 (8), pp.9442-9460
摘要:Abstract(#br)Quantification of pavement crack data is one of the most important criteria in determining optimum pavement maintenance strategies. Recently, multi-resolution analysis such as wavelet decompositions provides very good multi-resolution analytical tools for differ...
作者:Fereidoon Moghadas Nejad , Hamzeh Zakeri
来源:[J].Expert Systems With Applications(IF 1.854), 2011, Vol.38 (6), pp.7088-7101
摘要:... Recently, multi-resolution analysis such as wavelet decompositions provides very good multi-resolution analytical tools for different scales of pavement analysis and distresses classification. In this paper an expert system is proposed for pavement distress classification. A ...
作者:Wai Yeung Yan , X.-X. Yuan
来源:[J].Journal of Intelligent Transportation Systems(IF 0.806), 2018, Vol.22 (5), pp.376-389
摘要:ABSTRACT(#br)This study investigates the use of consumer-grade video camera to develop a low-cost pavement distress screening system, with a particular focus on low-volume roads. Due to the oblique view of video data captured in the car front, existing crack detection algorithms ...
作者:Sue Ahn , Srivatsav Kandala , J. Uzan ...
来源:[J].Road Materials and Pavement Design(IF 0.642), 2011, Vol.12 (1), pp.195-216
摘要:ABSTRACT(#br)This study examines the adequacy of using conventional traffic data and national default values in the absence of weigh-in-motion (WIM) data for pavement design. A comparative study was conducted on 14 unique sections in Arizona (AZ), where WIM data are available thr...
作者:H.D. Cheng , M. Miyojim
来源:[J].Information Sciences(IF 3.643), 1998, Vol.108 (1), pp.219-240
摘要:Abstract(#br)Statistics published by the Federal Highway Administration indicates that maintenance and rehabilitation of highway pavements in the United States requires over $17 billion a year. Conventional visual and manual pavement distress analysis approaches that the inspecto...
作者:Yuchuan Du , Zihang Weng , Chenglong Liu ...
来源:[J].Journal of Advanced Transportation(IF 0.733), 2020, Vol.2020
摘要:Camera-based pavement distress detection plays an important role in pavement maintenance. Duplicate collections for the same distress and multiple overlaps of defects are both practical problems that greatly affect the detection results. In this paper, we propose a fine-grained f...
作者:Kasthurirangan Gopalakrishnan , Siddhartha K. Khaitan , Alok Choudhary ...
来源:[J].Construction and Building Materials(IF 2.293), 2017, Vol.157, pp.322-330
摘要:Abstract(#br)Automated pavement distress detection and classification has remained one of the high-priority research areas for transportation agencies. In this paper, we employed a Deep Convolutional Neural Network (DCNN) trained on the ‘big data’ ImageNet database, which co...
作者:Laura Inzerillo , Gaetano Di Mino , Ronald Roberts
来源:[J].Automation in Construction(IF 1.82), 2018, Vol.96, pp.457-469
摘要:Abstract(#br)On local and urban networks, the enduring issue of scarce resources for Maintenance, Rehabilitation, and Reconstruction strategies (MR&R) has led, in many cases, to using unadjusted or poor techniques for road pavement distress detection and analysis, yielding ineffe...

我们正在为您处理中,这可能需要一些时间,请稍等。

资源合作:cnki.scholar@cnki.net, +86-10-82896619   意见反馈:scholar@cnki.net

×