Cargando…
Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer
Road surfaces should be maintained in excellent condition to ensure the safety of motorists. To this end, there exist various road-surface monitoring systems, each of which is known to have specific advantages and disadvantages. In this study, a smartphone-based dual-acquisition method system capabl...
Autores principales: | Lee, Taehee, Chun, Chanjun, Ryu, Seung-Ki |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830004/ https://www.ncbi.nlm.nih.gov/pubmed/33466847 http://dx.doi.org/10.3390/s21020561 |
Ejemplares similares
-
Classification and Segmentation of Longitudinal Road Marking Using Convolutional Neural Networks for Dynamic Retroreflection Estimation
por: Chun, Chanjun, et al.
Publicado: (2020) -
Road Surface Damage Detection Using Fully Convolutional Neural Networks and Semi-Supervised Learning
por: Chun, Chanjun, et al.
Publicado: (2019) -
Road Surface Anomaly Assessment Using Low-Cost Accelerometers: A Machine Learning Approach
por: Martinelli, Alessio, et al.
Publicado: (2022) -
Assessing and Mapping of Road Surface Roughness based on GPS and Accelerometer Sensors on Bicycle-Mounted Smartphones
por: Zang, Kaiyue, et al.
Publicado: (2018) -
Smartphone Sensing of Road Surface Condition and Defect Detection
por: Dong, Dapeng, et al.
Publicado: (2021)