The prediction of pedestrian behavior is essential for automated driving in urban traffic and
has attracted increasing attention in the vehicle industry. This task is challenging because …

Autonomous vehicles (AV) s have become a trending topic nowadays since they have the
potential to solve traffic problems, such as accidents and congestion. Although AV systems …

Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …

For autonomous driving, one of the major challenges is to predict pedestrian crossing
intention in ego-view. Pedestrian intention depends not only on their intrinsic goals but also …

Fabric defect detection is particularly remarkable because of the large textile production
demand in China. Traditional manual detection method is inefficient, time‐consuming …

Estimating when pedestrians cross the street is essential for intelligent transportation
systems. Accurate, real-time prediction is critical to ensure the safety of the most vulnerable …

Forecasting pedestrian trajectories is widely used in mobile agents such as self-driving
vehicles and social robots. Deep neural network-based trajectory prediction models …

Anticipating pedestrian crossing behavior in urban scenarios is a challenging task for
autonomous vehicles. Early this year, a benchmark comprising JAAD and PIE datasets have …

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

Recent research on pedestrian trajectory prediction based on deep learning has made
significant progress. However, the previous methods do not deeply explore the relationship …