Results 31 to 40 of about 9,841 (297)

Pavement Crack Detection Using Convolutional Neural Network

EPiC Series in Computing, 2020
Automating the process of detecting pavement cracks became a challenge mission. In the last few decades, many methods were proposed to solve this problem. The reason is that maintaining a stable condition of roads is essential for the safety of people and public properties.
Alaa F. Sheta, Hamza Turabieh, Sultan Aljahdali, Abdulaziz Alangari   +3 more
openaire   +2 more sources

End-to-End Pavement Crack Detection Method Based on Transformer

Taiyuan Ligong Daxue xuebao, 2022
Aiming at the problem of low detection accuracy caused by irregular crack shape and complex background in pavement crack detection scene, an end-to-end pavement crack detection method based on transformer, CrackFormerNet, was proposed.
Jun LIU, Huimin WANG, Xingzhong ZHANG, Ting ZHANG, Meiqing GUO   +4 more
doaj   +1 more source

Review: optical fiber sensors for civil engineering applications [PDF]

, 2013
Optical fiber sensor (OFS) technologies have developed rapidly over the last few decades, and various types of OFS have found practical applications in the field of civil engineering. In this paper, which is resulting from the work of the RILEM technical
B Poumellec, BJ Soller, C Lan, C Vimer, Christopher K. Y. Leung, CKY Leung, D Culverhouse, D Inaudi, D Inaudi, D Li, Daniele Inaudi, F Ansari, F Ravet, F Ravet, G Meltz, H Li, H Zhu, Hwai Chung Wu, J He, Jinping Ou, JP Dakin, Kai Tai Wan, KO Hill, KO Hill, KT Wan, KT Wan, KT Wan, KT Wan, KY Song, L Zou, L Zou, L Zou, M Froggatt, M Ghandehari, M Ghandehari, M Huang, M Tateda, Masoud Ghandehari, Michio Imai, MR Mokhtar, P Rossi, PJ Kajenski, PJS Cruz, PL Fuhr, PL Fuhr, PL Fuhr, Q Yu, R Brönnimann, S Liehr, SA Kingsley, SF Masri, T Horiguchi, T Horiguchi, Wolfgang Habel, WR Habel, X Bao, X Bao, X Gu, X Gu, Xiaoyi Bao, Y Rao, YG Lu, YQ Ni, Z Zhou, Zhi Zhou   +64 more
core   +2 more sources

Cracking in asphalt materials [PDF]

, 2018
This chapter provides a comprehensive review of both laboratory characterization and modelling of bulk material fracture in asphalt mixtures. For the purpose of organization, this chapter is divided into a section on laboratory tests and a section on ...
AF Braham, Armelle Chabot, B Behnia, B Birgisson, B Delaporte, B Kim, BS Underwood, C Huet, D Bodin, D Bodin, Didier Bodin, DV Ramsamooj, Emmanuel Chailleux, Eshan V. Dave, Eshan V. Dave, Eshan V. Dave, F Dubois, F Dubois, F Dubois, F Jiang, GR Chehab, H Benedetto Di, H Benedetto Di, H Lemaistre, HJ Lee, HM Nguyen, J Mandel, JF Corte, JS Daniel, K Majidzadeh, Malcolm L. Williams, MJ Jacobs, MJ Lamborn, MP Wagoner, MP Wagoner, N Tapsoba, NH Gibson, R Roque, R Roque, R. A. Schapery, RA Schapery, RA Schapery, RA Schapery, S Ahmed, S Ahmed, S Ahmed, SH Song, Simon Pouget, SW Park, T Hou, Xinjun Li, YR Kim, YR Kim, YR Kim, YR Kim, Z Zhang, Z Zhang   +56 more
core   +5 more sources

Evaluation of the techniques to mitigate early shrinkage cracking through an image analysis methodology [PDF]

, 2016
This is the accepted version of the following article: [Ruiz-Ripoll, L., Barragán, B. E., Moro, S., and Turmo, J. (2016) Evaluation of the Techniques to Mitigate Early Shrinkage Cracking through an Image Analysis Methodology. Strain, 52: 492–502. doi: 10.
Barragán, Bryan Erick, Moro, Sandro, Ruiz Ripoll, Lidia, Turmo Coderque, José   +3 more
core   +2 more sources

Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment

IEEE Access, 2021
Pavement cracks are severely affecting highway performance. Thus, implementing high-precision highway pavement crack detection is important for highway maintenance.
Kun Yan, Zhihua Zhang
doaj   +1 more source

Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding

, 2019
Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and labor-intensive.
Bocus, Mohammud Junaid, Cheng, Shanshan, Fan, Rui, Jiao, Jianhao, Liu, Ming, Ma, Fulong, Wang, Li, Zhu, Yilong   +7 more
core   +1 more source

A Framework for Automated Pavement Condition Monitoring [PDF]

, 2016
Pavement condition monitoring is mainly performed manually. Inspectors are driving or walking the road network bare eyed to look for irregularities. Moreover, processing the collected data for understanding the road condition is also a manual task.
,, Brilakis, I, Doycheva, K, Koch, C, Radopoulou, SC   +4 more
core   +2 more sources

Adaptive Road Crack Detection System by Pavement Classification

Sensors, 2011
This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks.
Miguel Gavilán, David Balcones, Oscar Marcos Martín, David Fernández Llorca, Miguel Ángel Sotelo, Ignacio Parra, Manuel Ocaña, Pedro Aliseda, Pedro Yarza, Alejandro Amírola   +9 more
openaire   +3 more sources

NHA12D: A new pavement crack dataset and a comparison study of crack detection algorithms

Computing in Construction, 2022
Crack detection plays a key role in automated pavement inspection. Although a large number of algorithms have been developed in recent years to further boost performance, there are still remaining challenges in practice, due to the complexity of pavement images.
Huang, Zhening, Chen, weiwei, Al-Tabbaa, Abir, Brilakis, Ioannis   +3 more
openaire   +3 more sources