Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
In the realm of machine learning (ML) systems featuring client-host connections, the
enhancement of privacy security can be effectively achieved through federated learning (FL) …
enhancement of privacy security can be effectively achieved through federated learning (FL) …
Partition placement and resource allocation for multiple DNN-based applications in heterogeneous IoT environments
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 …
neural network (DNN)-based applications and processing demands. Hence, edge …
ACF: An Adaptive Compression Framework for Multimodal Network in Embedded Devices
The ubiquitous Internet-of-Things (IoT) devices generate vast amounts of multimodal data,
and the deep multimodal fusion network (DMFN) is a promising technology for processing …
and the deep multimodal fusion network (DMFN) is a promising technology for processing …
Leveraging Deep Learning to Strengthen the Cyber-Resilience of Renewable Energy Supply Chains: A Survey
MN Halgamuge - IEEE Communications Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Deep learning shows immense potential for strengthening the cyber-resilience of renewable
energy supply chains. However, research gaps in comprehensive benchmarks, real-world …
energy supply chains. However, research gaps in comprehensive benchmarks, real-world …
RL-DistPrivacy: Privacy-aware distributed deep inference for low latency IoT systems
Although Deep Neural Networks (DNN) have become the backbone technology of several
ubiquitous applications, their deployment in resource-constrained machines, eg, Internet of …
ubiquitous applications, their deployment in resource-constrained machines, eg, Internet of …
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey
With the rapid growth in the volume of data sets, models, and devices in the domain of deep
learning, there is increasing attention on large-scale distributed deep learning. In contrast to …
learning, there is increasing attention on large-scale distributed deep learning. In contrast to …
A hybrid fast inference approach with distributed neural networks for edge computing enabled UAV swarm
Nowadays, unmanned aerial vehicle (UAV) swarm supported by mobile edge computing is
attracting more and more attention, such as smart agriculture, smart transportation, smart …
attracting more and more attention, such as smart agriculture, smart transportation, smart …
Optimal resource management for hierarchical federated learning over HetNets with wireless energy transfer
Remote monitoring systems analyze the environment dynamics in different smart industrial
applications, such as occupational health and safety, and environmental monitoring …
applications, such as occupational health and safety, and environmental monitoring …
Green Edge AI: A Contemporary Survey
Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
Model Lightweighting for Real‐time Distraction Detection on Resource‐Limited Devices
J Wang, ZC Wu - Computational Intelligence and Neuroscience, 2022 - Wiley Online Library
Detecting distracted driving accurately and quickly with limited resources is an essential yet
underexplored problem. Most of the existing works ignore the resource‐limited reality. In this …
underexplored problem. Most of the existing works ignore the resource‐limited reality. In this …