Girma et al., 2019 - Google Patents
Driver identification based on vehicle telematics data using LSTM-recurrent neural networkGirma et al., 2019
View PDF- Document ID
- 1037795552888977331
- Author
- Girma A
- Yan X
- Homaifar A
- Publication year
- Publication venue
- 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)
External Links
Snippet
Despite advancements in vehicle security systems, over the last decade, auto-theft rates have increased, and cyber-security attacks on internet-connected and autonomous vehicles are becoming a new threat. In this paper, a deep learning model is proposed, which can …
- 230000001537 neural 0 title description 16
Classifications
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G—PHYSICS
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- G06K9/46—Extraction of features or characteristics of the image
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- G—PHYSICS
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- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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- G06Q10/00—Administration; Management
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