In this study, an attention-based deep neural network (ADNet) method is proposed for driver behavior recognition. The ADNet framework is first presented, which ...
Jul 1, 2022 · In this study, an attention-based deep neural network (ADNet) method is proposed for driver behavior recognition. The ADNet framework is first ...
Feb 2, 2024 · Attention-based deep neural network for driver behavior recognition ... network (ADNet) method is proposed for driver behavior recognition ...
Aug 1, 2019 · Driving behavior recognition is a challenging task that exploits the acceleration and angular velocity information of the vehicle collected ...
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... deep learning-based distracted driving behavior recognition ... [40] proposed a soft spatial attention network based on deep learning for driver action ...
Aug 4, 2022 · In this paper, we use a driver dataset from State Farm for testing, and use 75% of this dataset for training and 25% for testing. The driver ...
Constructed by transfer learning and supervised learning, the convolutional neural network model can recognize driving behaviors such as calling and smoking [3] ...
Sep 30, 2022 · The basic idea of this method is to perform attention imaging analysis on the neural network virtual driver based on the vehicle driving state ...
We propose hierarchical actions and an attention mechanism to generate lane change behavior. We use the TORCS simulation environment. information. Similarly, ...
A curated list of peer-reviewed papers on theoretical and practical aspects of drivers' attention used for paper "Attention for Vision-Based Assistive and ...