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Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder
Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856181/ https://www.ncbi.nlm.nih.gov/pubmed/29462931 http://dx.doi.org/10.3390/s18020608 |