Machine-learned features from smartphone accelerometers can detect road anomalies and aggressive driving, with bag-of-words shapelets beating hand-crafted descriptors by over 5% in accuracy and F-measure.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Machine Learning Approach for Smartphone-based Sensing of Roads and Driving Style
Machine-learned features from smartphone accelerometers can detect road anomalies and aggressive driving, with bag-of-words shapelets beating hand-crafted descriptors by over 5% in accuracy and F-measure.