Cargando…

An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data

Road surface monitoring and maintenance are essential for driving comfort, transport safety and preserving infrastructure integrity. Traditional road condition monitoring is regularly conducted by specially designed instrumented vehicles, which requires time and money and is only able to cover a lim...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wu, Chao, Wang, Zhen, Hu, Simon, Lepine, Julien, Na, Xiaoxiang, Ainalis, Daniel, Stettler, Marc
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583950/ https://www.ncbi.nlm.nih.gov/pubmed/32998427 http://dx.doi.org/10.3390/s20195564

Ejemplares similares

VIDAR-Based Road-Surface-Pothole-Detection Method
por: Xu, Yi, et al.
Publicado: (2023)

The Road to Ribosomes: Filling Potholes in the Export Pathway
por: Aitchison, John D., et al.
Publicado: (2000)

Comparative Study on Distributed Lightweight Deep Learning Models for Road Pothole Detection
por: Tahir, Hassam, et al.
Publicado: (2023)

Taenia solium control in Zambia: The potholed road to success
por: Gabriël, S., et al.
Publicado: (2018)

Detection of Road Potholes by Applying Convolutional Neural Network Method Based on Road Vibration Data
por: Ozoglu, Furkan, et al.
Publicado: (2023)

Smart Pothole Detection Using Deep Learning Based on Dilated Convolution
por: Ahmed, Khaled R.
Publicado: (2021)

An annotated water-filled, and dry potholes dataset for deep learning applications
por: Dib, Jihad, et al.
Publicado: (2023)

Pothole Detection System Using a Black-box Camera
por: Jo, Youngtae, et al.
Publicado: (2015)

Computer Vision Based Pothole Detection under Challenging Conditions
por: Bučko, Boris, et al.
Publicado: (2022)

Gene–Environment Interaction in the Era of Precision Medicine – Filling the Potholes Rather Than Starting to Build a New Road
por: Álvarez-Castro, José M.
Publicado: (2020)

Spontaneous Pothole Cardioversion of a Wide Complex Tachycardia
por: Freeman, Wilbur K., et al.
Publicado: (2020)

Corrigendum: Gene-environment interaction in the era of precision medicine—filling the potholes rather than starting to build a new road
por: Álvarez-Castro, José M.
Publicado: (2023)

Wall Street potholes: insights from top money managers on avoiding dangerous products
por: Lack, Simon
Publicado: (2016)

Widespread Use and Frequent Detection of Neonicotinoid Insecticides in Wetlands of Canada's Prairie Pothole Region
por: Main, Anson R., et al.
Publicado: (2014)

Improvement of Tiny Object Segmentation Accuracy in Aerial Images for Asphalt Pavement Pothole Detection
por: Kim, Sujong, et al.
Publicado: (2023)

Patterns and drivers for wetland connections in the Prairie Pothole Region, United States
por: Vanderhoof, Melanie K., et al.
Publicado: (2016)

Road Surface Monitoring Using Smartphone Sensors: A Review
por: Sattar, Shahram, et al.
Publicado: (2018)

Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor
por: Du, Ronghua, et al.
Publicado: (2020)

Correction: Widespread Use and Frequent Detection of Neonicotinoid Insecticides in Wetlands of Canada's Prairie Pothole Region
Publicado: (2014)

Vulnerability of Breeding Waterbirds to Climate Change in the Prairie Pothole Region, U.S.A
por: Steen, Valerie, et al.
Publicado: (2014)

Waterfowl Conservation in the US Prairie Pothole Region: Confronting the Complexities of Climate Change
por: Niemuth, Neal D., et al.
Publicado: (2014)

Invasive Species Change Plant Community Composition of Preserved Prairie Pothole Wetlands
por: Jones, Seth A., et al.
Publicado: (2023)

A Robotized Raspberry-Based System for Pothole 3D Reconstruction and Mapping
por: Bruno, Salvatore, et al.
Publicado: (2023)

Driver behavior profiling: An investigation with different smartphone sensors and machine learning
por: Ferreira, Jair, et al.
Publicado: (2017)

The Role of Lake Expansion in Altering the Wetland Landscape of the Prairie Pothole Region, United States
por: Vanderhoof, Melanie K., et al.
Publicado: (2015)

Flood Routing Model Coupled with Dynamic Leakage Losses for Ephemeral Rivers with Large Potholes
por: Liu, Congmin, et al.
Publicado: (2022)

Identification and Analysis of Weather-Sensitive Roads Based on Smartphone Sensor Data: A Case Study in Jakarta
por: Yang, Chao-Lung, et al.
Publicado: (2021)

An Architectural Multi-Agent System for a Pavement Monitoring System with Pothole Recognition in UAV Images
por: Silva, Luís Augusto, et al.
Publicado: (2020)

Using a vegetation index to assess wetland condition in the Prairie Pothole Region of North America
por: Tangen, Brian A., et al.
Publicado: (2022)

Smartphone Sensing of Road Surface Condition and Defect Detection
por: Dong, Dapeng, et al.
Publicado: (2021)

A Machine Learning Framework for Automated Accident Detection Based on Multimodal Sensors in Cars
por: Hozhabr Pour, Hawzhin, et al.
Publicado: (2022)

Evaluation of automated anthropometrics produced by smartphone-based machine learning: a comparison with traditional anthropometric assessments
por: Graybeal, Austin J., et al.
Publicado: (2023)

Evidence for 20th century climate warming and wetland drying in the North American Prairie Pothole Region
por: Werner, Brett A, et al.
Publicado: (2013)

Assessing and Mapping of Road Surface Roughness based on GPS and Accelerometer Sensors on Bicycle-Mounted Smartphones
por: Zang, Kaiyue, et al.
Publicado: (2018)

Machine Learning Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor
por: Ng, Hui R., et al.
Publicado: (2022)

Automated detection of the yellow‐legged hornet (Vespa velutina) using an optical sensor with machine learning
por: Herrera, Cayetano, et al.
Publicado: (2022)

Automated Machine Learning
por: Masood, Adnan, et al.
Publicado: (2021)

Beyond Where to How: A Machine Learning Approach for Sensing Mobility Contexts Using Smartphone Sensors (†)
por: Guinness, Robert E.
Publicado: (2015)

Estimating the Standing Long Jump Length from Smartphone Inertial Sensors through Machine Learning Algorithms
por: De Lazzari, Beatrice, et al.
Publicado: (2023)

AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network
por: Singh, Abhilash, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_t1kvl1icuf69rt44qnjqna8pcd