Video analytics with deep learning techniques has generated immense interest in academia
and industry, captivating minds with its transformative potential. Deep learning techniques …

Video, as a key driver in the global explosion of digital information, can create tremendous
benefits for human society. Governments and enterprises are deploying innumerable …

The Internet of Vehicles (IoV) has become a fundamental platform for advancing Intelligent
Transportation Systems (ITSs) and Intelligent Connected Vehicles (ICVs). However, the …

Edge computing has been widely applied in video streaming systems, aiming to provide low-
latency video streaming services. However, limited resources and a lack of incentivization …

Serverless computing is envisioned as the de-facto standard for next-generation cloud
computing. However, the cold start dilemma has impeded its adoption by delay-sensitive …

In Mobile Edge Computing (MEC), the collaboration between end devices and servers
guarantees the low-latency and high-accuracy video stream analysis. However, such …

Cameras are widely used in many fields, eg, intelligent transportation, autonomous driving,
surveillance, etc. It is thus vital to conduct video analytics in an efficient and accurate …

The evolution of the Internet of Things (IoT) has been driving the explosive growth of deep
neural network (DNN)-based applications and processing demands. Hence, edge …

Edge computing has emerged as a powerful technology for enhancing the performance of
on-device video analytics, which is critical to support real-time applications. Nevertheless …

Driven by the Quality of Experience (QoE) demands for video analysis applications within
contexts such as smart cities, Industrial Internet of Things (IoT), and Internet of Vehicles …