Deep learning with edge computing: A review
Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …
and natural language processing. End devices, such as smartphones and Internet-of-Things …
A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective
A Shakarami, M Ghobaei-Arani, A Shahidinejad - Computer Networks, 2020 - Elsevier
With the rapid developments in emerging mobile technologies, utilizing resource-hungry
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
Edge intelligence: Empowering intelligence to the edge of network
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …
caching, processing, and analysis proximity to where data are captured based on artificial …
Deep learning-based object detection in augmented reality: A systematic review
Recent advances in augmented reality (AR) and artificial intelligence have caused these
technologies to pioneer innovation and alteration in any field and industry. The fast-paced …
technologies to pioneer innovation and alteration in any field and industry. The fast-paced …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
DMRO: A deep meta reinforcement learning-based task offloading framework for edge-cloud computing
With the explosive growth of mobile data and the unprecedented demand for computing
power, resource-constrained edge devices cannot effectively meet the requirements of …
power, resource-constrained edge devices cannot effectively meet the requirements of …
Deepdecision: A mobile deep learning framework for edge video analytics
Deep learning shows great promise in providing more intelligence to augmented reality (AR)
devices, but few AR apps use deep learning due to lack of infrastructure support. Deep …
devices, but few AR apps use deep learning due to lack of infrastructure support. Deep …
Deep learning based object detection for resource constrained devices: Systematic review, future trends and challenges ahead
Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …
performance. However, the majority of applications that require object detection are …
Pervasive AI for IoT applications: A survey on resource-efficient distributed artificial intelligence
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of
Things (IoT) applications and services, spanning from recommendation systems and speech …
Things (IoT) applications and services, spanning from recommendation systems and speech …
[HTML][HTML] A survey on deploying mobile deep learning applications: A systemic and technical perspective
With the rapid development of mobile devices and deep learning, mobile smart applications
using deep learning technology have sprung up. It satisfies multiple needs of users, network …
using deep learning technology have sprung up. It satisfies multiple needs of users, network …