Pavement Patch Defects Detection and Classification Using Smartphones, Vibration Signals and Video Images-Reference-Cited by-同舟云学术

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Pavement Patch Defects Detection and Classification Using Smartphones, Vibration Signals and Video Images

Published:2019 Issue: Volume: Page:365-380
ISSN:
Container-title:Mobility Patterns, Big Data and Transport Analytics
language:
Short-container-title:

Author:

Christodoulou Symeon E.,Kyriakou Charalambos,Hadjidemetriou George

Publisher

Elsevier

Reference23 articles.

1. SmartRoadSense: collaborative road surface condition monitoring;Alessandroni,2014

2. Precision bounds of pavement deterioration forecasts from connected vehicles;Bridgelall;J. Infrastruct. Syst.,2015

3. Estimating the Effects of Pavement Condition on Vehicle Operating Costs;Chatti,2012

4. EU Road Surfaces: Economic and Safety Impact of the Lack of Regular Road Maintenance;Gleave,2014

5. Automated detection of pavement patches utilizing support vector machine classification;Hadjidemetriou,2016

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1. A Conceptual Framework for Mobility Data Science;IEEE Access;2024

2. On the performance of pothole detection algorithms enhanced via data augmentation;Transportation Research Procedia;2024

3. Predicting Road Condition using Linear Hierarchical Modelling;IFAC-PapersOnLine;2024

4. Pavement Distress Identification Based on Computer Vision and Controller Area Network (CAN) Sensor Models;Sustainability;2023-04-10

5. Design and Implementation of a Vibration-Based Real-Time Internet of Things Framework for Road Condition Monitoring;IEEE Open Journal of Vehicular Technology;2023

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