Environmental perception is a key element of autonomous driving because the information
received from the perception module influences core driving decisions. An outstanding …

Environmental perception is a key element of autonomous driving because the information
received from the perception module influences core driving decisions. An outstanding …

Deep Neural-Network (DNN) based Object Detection is one of the most important and time-
consuming stages of Autonomous Driving software in cars. In non-critical domains, the …

Computer vision tasks such as object detection are crucial for the operations of autonomous
vehicles (AVs). Results of many tasks, even those requiring high computational power, can …

For Internet of Vehicles applications, reliable autonomous driving systems usually perform
the majority of their computations on the cloud due to the limited computing power of edge …

In model partitioning for real-time object detection, part of the model is deployed on a
vehicle, and the remaining layers are processed in the cloud. Model partitioning requires …

Object detection is a crucial task for autonomous driving. In addition to requiring high
accuracy to ensure safety, object detection for autonomous driving also requires real-time …

For realizing safe autonomous driving, the end-to-end delays of real-time object detection
systems should be thoroughly analyzed and minimized. However, despite recent …

Enabling a computer to extract information from digital images or videos falls into the field of
computer vision (CV). This field is rapidly growing along-side the rise of deep learning and is …

Fully autonomous driving systems require fast detection and recognition of sensitive objects
in the environment. In this context, intelligent vehicles should share their sensor data with …