No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Medical data are present in large amount and this is difficult to process for the diagnosis and
Healthcare organization requires effective technique to handle big data. Existing techniques …

In remote sensing images, change detection (CD) is required in many applications, such as:
resource management, urban expansion research, land management, and disaster …

Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …

Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …

Scene classification aims to classify various objects and land use classes such as farms,
highways, rivers, and airplanes in the remote sensing images. In recent times, the …

Mobility trajectory data is of great significance for mobility pattern study, urban computing,
and city science. Self-driving, traffic prediction, environment estimation, and many other …

Intersections are quite important and complex traffic scenarios, where the future motion of
surrounding vehicles is an indispensable reference factor for the decision-making or path …

Human trajectory forecasting in crowds presents the challenges of modelling social
interactions and outputting collision-free multimodal distribution. Following the success of …