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Found 12 papers, 1 papers with code
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation
Remote sensing semantic segmentation (RSS) is an essential task in Earth Observation missions.
Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
Multimodal federated learning (FL) aims to enrich model training in FL settings where clients are collecting measurements across multiple modalities.
FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication
Multimodal federated learning (FL) aims to enrich model training in FL settings where devices are collecting measurements across multiple modalities (e. g., sensors measuring pressure, motion, and other types of data).
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges
This survey paper presents a review of the advancements made in the application of FL for CAV (FL4CAV).
Decentralized Federated Learning: A Survey and Perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while maintaining user data, protecting privacy, increasing learning efficiency, and reducing communication overhead.
Smart Pressure e-Mat for Human Sleeping Posture and Dynamic Activity Recognition
Deep neural networks (DNNs) are used to fit and train the pressure image stream and recognize the corresponding human behavior.
M$^2$DAR: Multi-View Multi-Scale Driver Action Recognition with Vision Transformer
Ensuring traffic safety and preventing accidents is a critical goal in daily driving, where the advancement of computer vision technologies can be leveraged to achieve this goal.
Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition
Naturalistic driving action recognition (NDAR) has proven to be an effective method for detecting driver distraction and reducing the risk of traffic accidents.
Passive Radio Frequency-based 3D Indoor Positioning System via Ensemble Learning
Passive radio frequency (PRF)-based indoor positioning systems (IPS) have attracted researchers' attention due to their low price, easy and customizable configuration, and non-invasive design.
A Survey of Federated Learning for Connected and Automated Vehicles
Connected and Automated Vehicles (CAVs) are one of the emerging technologies in the automotive domain that has the potential to alleviate the issues of accidents, traffic congestion, and pollutant emissions, leading to a safe, efficient, and sustainable transportation system.
Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application
This paper proposes a federated transfer-ordered-personalized learning (FedTOP) framework to address the above problems and test on two real-world datasets with and without system heterogeneity.
