Passenger counting is crucial for many applications such as vehicle scheduling and traffic
capacity assessment. However, most of the existing solutions are either high-cost, privacy …

Weather detection systems (WDS) have an indispensable role in supporting the decisions of
autonomous vehicles, especially in severe and adverse circumstances. With deep learning …

The eye-blink pattern is crucial for drowsy driving diagnostics, which has become an
increasingly serious social issue. However, traditional methods (eg, with EOG, camera …

Driver drowsiness is a significant factor in road crashes. However, existing solutions for
driver drowsiness detection have major drawbacks of requiring special hardware …

Dangerous driving behaviors are the main cause of most traffic accidents, and the detection
of these behaviors is one of the extremely important researches in Intelligent Transportation …

Recent years have witnessed the rapid boom of mobile devices interweaving with changes
the epidemic has made to people's lives. Though a tremendous amount of novel human …

Acoustic target tracking has shown great advantages for device-free human-machine
interaction over vision/RF-based mechanisms. However, existing approaches for portable …

Blink detection is essential for various human-computer interaction scenarios, such as virtual
reality and driving state detection. It has gained significant attention from industry and …

Although micro-mobility brings convenience to modern cities, they also cause various social
problems, such as traffic accidents, casualties, and substantial economic losses. Wearing …

Driver maneuver interaction learning (DMIL) refers to the classification task with the goal of
identifying different driver-vehicle maneuver interactions (eg, left/right turns). Existing …