Attention-Based Event Characterization for Scarce Vehicular Sensing Data

Attention-Based Event Characterization for Scarce Vehicular Sensing Data

Characterizing risky driving behavior is crucial in a connected vehicle environment, particularly to improve driving experience through enhanced safety features. Artificial intelligence-backed solutions are vital components of the modern transportation. However, such systems require significant volu...

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Bibliographic Details
Main Authors: Nima Taherifard, Murat Simsek, Charles Lascelles, Burak Kantarci
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Open Journal of Vehicular Technology
Subjects:
Attention model
auto-encoder
connected vehicles
LSTM
machine learning
recurrent neural networks
Online Access:https://ieeexplore.ieee.org/document/9200673/

Internet

https://ieeexplore.ieee.org/document/9200673/

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