In driving scenes, road agents often engage in frequent interaction and strive to understand
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …

Road traffic accidents involving collisions between vehicles and pedestrians are a major
cause of death and injury globally. With recent technological progress in the field of …

As the development of autonomous driving technology continues, pedestrian safety is
becoming an increasingly important issue. The ability of an autonomous car to accurately …

Wafer map defect classification plays a crucial role in sustaining the semiconductor supply
chain during industrial disruptions by ensuring continuity, resilience, and efficiency while …

This review paper presents an in-depth analysis of deep learning (DL) models applied to
traffic scene understanding, a key aspect of modern intelligent transportation systems. It …

Accurately recognizing and predicting pedestrian intentions is crucial for autonomous
vehicle safety. However, existing prediction models often fail to comprehensively consider …

Understanding and predicting pedestrian crossing behavioral intention is crucial for
autonomous vehicles driving safety. Nonetheless, challenges emerge when using promising …

The advent of autonomous vehicles necessitates sophisticated visual recognition systems
capable of interpreting traffic signs in real-time. Despite significant advancements …

With the development of deep learning technology, the problem of data‐driven trajectory
prediction and intention recognition has been widely studied. However, the pedestrian …

In cross-domain pedestrian trajectory prediction, most existing methods usually focus on
learning entangled spatial-temporal domain-invariant features, while ignoring the different …