The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Edge computing is an emerging paradigm for the increasing computing and networking
demands from end devices to smart things. Edge computing allows the computation to be …

Edge video analytics is becoming the solution to many safety and management tasks. Its
wide deployment, however, must first address the tension between inference accuracy and …

This paper discusses challenges in computer systems research posed by the emerging
autonomous driving systems. We first identify four research areas related to autonomous …

Machine learning-based software is vital for future Internet of Things (IoT) applications and
Connected and Autonomous Vehicles (CAVs) as it provides the core value of these services …

In recent years, deep learning (DL) models have demonstrated remarkable achievements
on non-trivial tasks such as speech recognition, image processing, and natural language …

Deep neural networks (DNNs) are widely used in autonomous driving due to their high
accuracy for perception, decision, and control. In safety-critical systems like autonomous …

This article presents the Network Empower and Prototyping Platform (NEP+), a flexible
framework purposefully crafted to simplify the process of interactive application …

In the last 5 years, with the vast improvements in computing technologies, eg, sensors,
computer vision, machine learning, and hardware acceleration, and the wide deployment of …