Federated learning on multimodal data: A comprehensive survey
With the growing awareness of data privacy, federated learning (FL) has gained increasing
attention in recent years as a major paradigm for training models with privacy protection in …
attention in recent years as a major paradigm for training models with privacy protection in …
Autofi: Toward automatic wi-fi human sensing via geometric self-supervised learning
Wi-Fi sensing technology has shown superiority in smart homes among various sensors for
its cost-effective and privacy-preserving merits. It is empowered by channel state information …
its cost-effective and privacy-preserving merits. It is empowered by channel state information …
An adaptive robust defending algorithm against backdoor attacks in federated learning
To address the backdoor attacks in federated learning due to the inherently distributed and
privacy-preserving peculiarities, we propose RDFL including four components: selecting the …
privacy-preserving peculiarities, we propose RDFL including four components: selecting the …
Fedlga: Toward system-heterogeneity of federated learning via local gradient approximation
Federated learning (FL) is a decentralized machine learning architecture, which leverages a
large number of remote devices to learn a joint model with distributed training data …
large number of remote devices to learn a joint model with distributed training data …
Airfi: empowering wifi-based passive human gesture recognition to unseen environment via domain generalization
WiFi-based smart human sensing technology enabled by Channel State Information (CSI)
has received great attention in recent years. However, CSI-based sensing systems suffer …
has received great attention in recent years. However, CSI-based sensing systems suffer …
Federated multi-task attention for cross-individual human activity recognition
Federated Learning (FL) is an emerging privacyaware machine learning technique that
applies successfully to the collaborative learning of global models for Human Activity …
applies successfully to the collaborative learning of global models for Human Activity …
RoPE: Defending against backdoor attacks in federated learning systems
Federated learning (FL) is vulnerable to backdoor attacks, which aim to cause the
misclassification on samples with a specific backdoor. Most existing algorithms are restricted …
misclassification on samples with a specific backdoor. Most existing algorithms are restricted …
A deep learning based lightweight human activity recognition system using reconstructed WiFi CSI
X Chen, Y Zou, C Li, W Xiao - IEEE Transactions on Human …, 2024 - ieeexplore.ieee.org
Human activity recognition (HAR) is a key technology in the field of human–computer
interaction. Unlike systems using sensors or special devices, the WiFi channel state …
interaction. Unlike systems using sensors or special devices, the WiFi channel state …
Wi-monitor: Daily activity monitoring using commodity wi-fi
S Zhou, L Guo, Z Lu, X Wen… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Daily activity monitoring is essential to healthy lifestyle assessment and personal healthcare,
among which Wi-Fi-based solutions have attracted increasing attention due to their no …
among which Wi-Fi-based solutions have attracted increasing attention due to their no …
Direction-independent human activity recognition using a distributed MIMO radar system and deep learning
Modern monostatic radar-based human activity recognition (HAR) systems perform very well
as long as the direction of human activities is either toward or away from the radar. The …
as long as the direction of human activities is either toward or away from the radar. The …