Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework
Author:
Affiliation:
1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
2. Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing, China
Funder
Key Research and Development Program of Shandong Province, China
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10202228/10101722.pdf?arnumber=10101722
Reference46 articles.
1. Vehicle Driving Behavior Recognition Based on Multi-View Convolutional Neural Network With Joint Data Augmentation
2. Learning from Imbalanced Data
3. An Unsupervised Approach for Inferring Driver Behavior From Naturalistic Driving Data
4. A study of the behavior of several methods for balancing machine learning training data
5. DR(eye)VE: A Dataset for Attention-Based Tasks with Applications to Autonomous and Assisted Driving
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