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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Vydané v:	IEEE transactions on vehicular technology Ročník 69; číslo 7; s. 6943 - 6951
Hlavní autori:	Hu, Jie, Zhang, Xiaoqin, Maybank, Stephen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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