The emerging vehicular connected applications, such as cooperative automated driving and
intersection collision warning, show great potentials to improve the driving safety, where …

This study offers a systematic literature review on the application of Convolutional Neural
Networks in Virtual Reality, Augmented Reality, Mixed Reality, and Extended Reality …

Today very few deep learning-based mobile augmented reality (MAR) applications are
applied in mobile devices because they are significantly energy-guzzling. In this paper, we …

Today, deep learning optimization is primarily driven by research focused on achieving high
inference accuracy and reducing latency. However, the energy efficiency aspect is often …

Extended reality (XR) is at the center of attraction in the research community due to the
emergence of augmented, mixed, and virtual reality applications. The performance of such …

Artificial intelligence (AI) has enabled a new paradigm of smart applications-changing our
way of living entirely. Many of these AI-enabled applications have very stringent latency …

Artificial intelligence is bringing ever new functionalities to the realm of mobile devices that
are now considered essential (eg, camera and voice assistants, recommender systems) …

Many mobile applications are now integrating deep learning models into their core
functionality. These functionalities have diverse latency requirements while demanding high …

Edge-assisted mobile augmented reality (Edge-MAR) systems have emerged as effective
ways to support computation-intensive and latency-sensitive applications for mobile devices …

Edge computing is proposed to be a promising paradigm to bridge the gap between the
stringent computation requirement of realtime mobile augmented reality (MAR) and the …