The advancement in deep learning and edge computing has enabled intelligent mobile
augmented reality (MAR) on resource limited mobile devices. However, today very few deep …

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

Applying deep learning to object detection provides the capability to accurately detect and
classify complex objects in the real world. However, currently, few mobile applications use …

With the rapid advancement of automobile industry, autonomous driving in connected
vehicles are expected to be the key technology to satisfy the expansion of human demands …

With the development of mobile augmented reality (MAR) technology, the demand for MAR
applications is increasing. However, MAR is rarely used in mobile devices due to its high …

Applying deep learning to object detection provides the capability to accurately detect and
classify complex objects in the real world. However, currently, few mobile applications use …

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 …

In disaster-affected areas, the lack of cellular network connectivity can be a matter of life and
death. To address this issue, we propose the use of an unmanned aerial vehicle (UAV) …

This study proposes a rotational flying communication drone, a UAV equipped with
rotational antenna and a wi-fi base station, to support communication between rescue teams …

The prevalence of computation-intensive and latency-sensitive mobile applications, such as
mobile augmented reality (MAR) and autonomous driving, has an utmost effect on resource …