Abnormal Driving Detection With Normalized Driving Behavior Data: A Deep Learning Approach

Abnormal driving may cause serious danger to both the driver and the public. Existing detectors of abnormal driving behavior are mainly based on shallow models, which require large quantities of labeled data. The acquisition and labelling of abnormal driving data are, however, difficult, labor-inten...

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Bibliographic Details

Published in:	IEEE transactions on vehicular technology Vol. 69; no. 7; pp. 6943 - 6951
Main Authors:	Hu, Jie, Zhang, Xiaoqin, Maybank, Stephen
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Abnormal driving detection Acceleration Adaptation models Algorithms Biological system modeling Data models Deep learning Feature extraction Machine learning Noise reduction stacked autoencoder Vehicles
ISSN:	0018-9545, 1939-9359
Online Access:	Get full text
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