Driver action recognition using deformable and dilated faster R-CNN with optimized region proposals
M Lu, Y Hu, X Lu - Applied Intelligence, 2020 - Springer
Distracted driver action is the main cause of road traffic crashes, which threatens the security
of human life and public property. Based on the observation that cues (like the hand holding …
of human life and public property. Based on the observation that cues (like the hand holding …
Feature refinement for image-based driver action recognition via multi-scale attention convolutional neural network
Y Hu, M Lu, X Lu - Signal Processing: Image Communication, 2020 - Elsevier
Driver distraction has currently been a global issue causing the dramatic increase of road
accidents and casualties. However, recognizing distracted driving action remains a …
accidents and casualties. However, recognizing distracted driving action remains a …
Driver activity recognition for intelligent vehicles: A deep learning approach
Driver decisions and behaviors are essential factors that can affect the driving safety. To
understand the driver behaviors, a driver activities recognition system is designed based on …
understand the driver behaviors, a driver activities recognition system is designed based on …
Driving behaviour recognition from still images by using multi-stream fusion CNN
Y Hu, M Lu, X Lu - Machine Vision and Applications, 2019 - Springer
Abnormal driving behaviour is a leading cause of serious traffic accidents threatening
human life and public property globally. In this paper, we investigate the use of a deep …
human life and public property globally. In this paper, we investigate the use of a deep …
Bidirectional posture-appearance interaction network for driver behavior recognition
Driver behavior recognition has become one of the most important tasks for intelligent
vehicles. This task, however, is very challenging since the background contents in real-world …
vehicles. This task, however, is very challenging since the background contents in real-world …
Coarse temporal attention network (cta-net) for driver's activity recognition
There is significant progress in recognizing traditional human activities from videos focusing
on highly distinctive actions involving discriminative body movements, body-object and/or …
on highly distinctive actions involving discriminative body movements, body-object and/or …
Attention-based deep neural network for driver behavior recognition
W Xiao, H Liu, Z Ma, W Chen - Future Generation Computer Systems, 2022 - Elsevier
Driver behavior recognition is crucial for traffic safety in intelligent transportation systems. To
understand the driver distraction behavior, deep learning methods has been used to learn …
understand the driver distraction behavior, deep learning methods has been used to learn …
Distracted driving detection based on the fusion of deep learning and causal reasoning
Distracted driving is one of the key factors that cause drivers to ignore potential road hazards
and then lead to accidents. Existing efforts in distracted behavior recognition are mainly …
and then lead to accidents. Existing efforts in distracted behavior recognition are mainly …
Toward extremely lightweight distracted driver recognition with distillation-based neural architecture search and knowledge transfer
The number of traffic accidents has been continuously increasing in recent years worldwide.
Many accidents are caused by distracted drivers, who take their attention away from driving …
Many accidents are caused by distracted drivers, who take their attention away from driving …
Deep learning-based hard spatial attention for driver in-vehicle action monitoring
Distracted driving is one of the main causes of deaths and injuries in the world. Monitoring
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …