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

With the advancement in intelligent devices, social media, and the Internet of Things,
staggering amounts of new data are being generated, and the pace is continuously …

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 …

Deploying deep learning (DL) models for visual recognition on embedded systems is often
constrained by their limited compute power and storage capacity and has stringent latency …

In this paper, we investigate the optimal configuration and dependence-aware task
assignment for multi-task edge video analytics. Multi-task video analytics involves multiple …

Real-time video analytics services aim to provide users with accurate recognition results
timely. However, existing studies usually fall into the dilemma between reducing delay and …

Neural-based super-resolution (SR) has achieved great success in enhancing image or
video quality, creating new opportunities for building bandwidth-efficient and high-accuracy …

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

Autonomous driving vehicles, leveraging on-board cameras for real-time surrounding
environment sensing, have boosted the development of safe and efficient transportation …

Abstract Machine learning has proliferated on many Internet-of-Things (IoT) applications
designed for edge devices. Energy efficiency is one of the most crucial constraints in the …