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

Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …

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 …

Ensuring a reliable perception of vulnerable road users is crucial for safe autonomous
driving. Radar stands out as an appealing sensor choice due to its resilience in adverse …

The task of annotating data into concise summaries poses a significant challenge across
various domains, frequently requiring the allocation of significant time and specialized …

Millimeter-wave (mmWave) radar sensors produce Point Clouds (PCs) that are much
sparser and noisier than other PC data (eg, Li-DAR), yet they are more robust in challenging …

In autonomous driving, accurately identifying traffic targets is crucial for ensuring the safe
and reliable operation of autonomous vehicles. Millimeter-wave radar, known for its low cost …

The rapid development of automated vehicles (AVs) promises to revolutionize transportation
by enhancing safety and efficiency. However, ensuring their reliability in diverse real-world …

Millimeter-wave (mmWave) radar has been widely applied in target detection. However, due
to multipath and occlusion, radar often detects ghosts, especially in indoor environments …

The unique properties of radar sensors, such as their robustness to adverse weather
conditions, make them an important part of the environment perception system of …