Design and Implementation of On-Device AI for Dangerous Driving Behavior Recognition
Author:
Affiliation:
1. Pusan National University,School of Computer Science and Engineering,Busan,Republic of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10217210/10217189/10217246.pdf?arnumber=10217246
Reference16 articles.
1. ID extraction OBD-II vehicle operation for driver behavior analysis;lim;The Proceedings of Korea Information and Communication Society,2018
2. Analysis of overtaking patterns of Indian drivers with data collected using a LiDAR
3. A Novel Lane-Changing Decision Model for Autonomous Vehicles Based on Deep Autoencoder Network and XGBoost
4. Video-Based Abnormal Driving Behavior Detection via Deep Learning Fusions
5. Gated Recurrent Fusion to Learn Driving Behavior from Temporal Multimodal Data
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