Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

With the rapid advancements of sensor technology and deep learning, autonomous driving
systems are providing safe and efficient access to intelligent vehicles as well as intelligent …

Autonomous driving on water surfaces plays an essential role in executing hazardous and
time-consuming missions, such as maritime surveillance, survivor rescue, environmental …

With the development of Unmanned Surface Vehicles (USVs), the perception of inland
waterways has become significant to autonomous navigation. RGB cameras can capture …

Radars and cameras belong to the most frequently used sensors for advanced driver
assistance systems and automated driving research. However, there has been surprisingly …

Urban water-surface robust perception serves as the foundation for intelligent monitoring of
aquatic environments and the autonomous navigation and operation of unmanned vessels …

Accurate and robust object detection is critical for autonomous driving. Image-based
detectors face difficulties caused by low visibility in adverse weather conditions. Thus, radar …

Accurately identifying and tracking different types of vehicles is the basis of safe driving of
intelligent vehicles. Because of the defects of the traditional rule-based association methods …

Due to millimeter-wave (MMW) radar's ability to directly acquire spatial positions and velocity
information of objects, as well as its robust performance in adverse weather conditions, it …

Unmanned surface vehicles (USVs) have been widely used for a wide range of tasks in the
past decades. Accurate perception of the surrounding environment on the water surface …