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1
RDD2020: An annotated image dataset for automatic road damage detection using deep learning
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RDD2020: An annotated image dataset for automatic road damage detection using deep learning

Data in brief, 2021-06, Vol.36, p.107133-107133, Article 107133 [Peer Reviewed Journal]

2021 ;2021 The Authors. Published by Elsevier Inc. 2021 ;ISSN: 2352-3409 ;EISSN: 2352-3409 ;DOI: 10.1016/j.dib.2021.107133 ;PMID: 34095382

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2
Development of Damage Functions on Road Infrastructures Subjected to Extreme Ground Excitations by Analyzing Damage in the 2011 off the Pacific Coast of Tohoku Earthquake
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Development of Damage Functions on Road Infrastructures Subjected to Extreme Ground Excitations by Analyzing Damage in the 2011 off the Pacific Coast of Tohoku Earthquake

Journal of disaster research, 2014-03, Vol.9 (2), p.121-127 [Peer Reviewed Journal]

ISSN: 1881-2473 ;EISSN: 1883-8030 ;DOI: 10.20965/jdr.2014.p0121

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3
DAMAGE LEVEL OF ROAD INFRASTRUCTURE AND ROAD TRAFFIC PERFORMANCE IN THE MID NIIGATA PREFECTURE EARTHQUAKE OF 2004
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DAMAGE LEVEL OF ROAD INFRASTRUCTURE AND ROAD TRAFFIC PERFORMANCE IN THE MID NIIGATA PREFECTURE EARTHQUAKE OF 2004

STRUCTURAL ENGINEERING / EARTHQUAKE ENGINEERING, 2007, Vol.24(1), pp.51s-61s

2007 by Japan Society of Civil Engineers ;ISSN: 0289-8063 ;EISSN: 1882-3424 ;DOI: 10.2208/jsceseee.24.51s

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