The data traffic volume of the 6th generation (6G) mobile communication networks is huge,
and there are novel challenges in various communications services and scenarios. This …

Autonomous driving vehicle (ADV) that is ready to transform our society and economy, is in
desperate need of precise positioning over itself as well as surrounding environments …

Mobile networks (MNs) are anticipated to provide unprecedented opportunities to enable a
new world of connected experiences and radically shift the way people interact with …

Object detection in traffic scenes has attracted considerable attention from both academia
and industry recently. Modern detectors achieve excellent performance under a simple …

Accurate spatial-temporal prediction is a fundamental building block of many real-world
applications such as traffic scheduling and management, environment policy making, and …

Brain tumor segmentation in medical imaging is a critical task for diagnosis and treatment
while preserving patient data privacy and security. Traditional centralized approaches often …

Multi-agent collaborative perception depends on sharing sensory information to improve
perception accuracy and robustness, as well as to extend coverage. The cooperative shared …

The use of multi-agent reinforcement learning (MARL) methods in coordinating traffic lights
(CTL) has become increasingly popular, treating each intersection as an agent. However …

The local parts of the target are vitally important for robust object tracking. Nevertheless,
existing excellent context regression methods involving siamese networks and …

In device-to-device (D2D) networks, multiple resource-limited mobile devices cooperate with
one another to execute computation tasks. As the battery capacity of mobile devices is …