Zobrazeno 1 - 9 of 9 pro vyhledávání: '"Offei Adarkwa"'
1
Akademický článek
An in-depth analysis of head-on crash severity and fatalities in Ghana
Autor: Emmanuel Kofi Adanu, William Agyemang, Abhay Lidbe, Offei Adarkwa, Steven Jones
Publikováno v: Heliyon, Vol 9, Iss 8, Pp e18937- (2023)
Head-on collisions are often linked to more serious injuries compared to other types of crashes, due to the intense impact they cause. In low- and middle-income countries, these collisions frequently involve high occupancy public transportation vehic
Externí odkaz: https://doaj.org/article/d95e9c42b8e14a108c94af730ae42cf9
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2
Akademický článek
Object Recognition in Aerial Images Using Convolutional Neural Networks
Autor: Matija Radovic, Offei Adarkwa, Qiaosong Wang
Publikováno v: Journal of Imaging, Vol 3, Iss 2, p 21 (2017)
There are numerous applications of unmanned aerial vehicles (UAVs) in the management of civil infrastructure assets. A few examples include routine bridge inspections, disaster management, power line surveillance and traffic surveying. As UAV applica
Externí odkaz: https://doaj.org/article/b1602c260e06418aa59570cac2d933ae
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4
Using Tensor Factorization to Predict Network-Level Performance of Bridges
Autor: Nii Attoh-Okine, Thomas Schumacher, Offei Adarkwa
Publikováno v: Journal of Infrastructure Systems. 23
The nation’s bridges are critical assets that facilitate travel and commerce, making them important components of economic growth. However, bridge repair and rehabilitation needs far exceed...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0b93e123a1859ce60703e2b5c7bc1234
https://doi.org/10.1061/(asce)is.1943-555x.0000339
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6
Prediction of Structural Deficiency Ratio of Bridges Based on Multiway Data Factorization
Autor: Nii Attoh-Okine, Offei Adarkwa
Publikováno v: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 3
Prediction of future bridge conditions is essential in bridge management as this provides guidance for strategic planning. The National Bridge Inventory (NBI) database has been used by researchers for this purpose by utilizing Markov Chains and regre
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::35bfc40e985756b7ade30d9be97bd240
https://doi.org/10.1061/ajrua6.0000882
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8
Pavement crack classification based on tensor factorization
Autor: Nii Attoh-Okine, Offei Adarkwa
Publikováno v: Construction and Building Materials. 48:853-857
This paper presents tensor factorization as a means of classifying cracks in pavements. Several crack classification algorithms exist and they are mostly based on other machine learning methods. These may come with their own problems which may be cla
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f5271e6ca1c8197382c95fa22a85fd04
https://doi.org/10.1016/j.conbuildmat.2013.07.091
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9
Multiway Analysis of bridge structural types in the National Bridge Inventory (NBI): A tensor decomposition approach
Autor: Thomas Schumacher, Nii Attoh-Okine, Offei Adarkwa
Publikováno v: BigData Conference
The National Bridge Inventory (NBI) has detailed information on over 600,000 bridges nationwide. The data, which spans a period of more than 20 years can be very useful for analyzing and modeling bridge performance. Previous analysis methods employ a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f30726281d32ba1af1ae41e01b4150ea
https://doi.org/10.1109/bigdata.2014.7004423
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