Deep learning-based intelligent vehicle perception has been developing prominently in
recent years to provide a reliable source for motion planning and decision making in …

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

Deep learning has been widely used in intelligent vehicle driving perception systems, such
as 3D object detection. One promising technique is Cooperative Perception, which …

Convolutional neural network (CNN)-based autonomous driving object detection algorithms
have excellent detection results on conventional datasets, but the detector performance can …

There are a large number of functional sensors installed on the modern intelligent vehicles.
Many Artificial Intelligence based foundation models have been proposed for smart sensing …

Medicinal chemistry and drug design efforts can be assisted by machine learning (ML)
models that relate the molecular structure to compound properties. Such quantitative …

In recent years, online distillation has emerged as a powerful technique for adapting real-
time deep neural networks on the fly using a slow, but accurate teacher model. However, a …

Due to the lack of real multi-agent data and time-consuming of labeling, existing multi-agent
cooperative perception algorithms usually select the simulated sensor data for training and …

Safety is critical for autonomous driving, and one aspect of improving safety is to accurately
capture the uncertainties of the perception system, especially knowing the unknown …

Car detection, especially through camera vision, has become a major focus in the field of
computer vision and has gained widespread adoption. While current car detection systems …