Exploring Federated Learning Tendencies Using a Semantic Keyword Clustering Approach
This paper presents a novel approach to analyzing trends in federated learning (FL) using
automatic semantic keyword clustering. The authors collected a dataset of FL research …
automatic semantic keyword clustering. The authors collected a dataset of FL research …
Community awareness personalized federated learning for defect detection
H Zhao, Q Liu, H Sun, L Xu, W Zhang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Multiple organizations in social manufacturing can collaborate on high-quality product defect
detection with social networks. Federated learning (FL) is an emerging paradigm where …
detection with social networks. Federated learning (FL) is an emerging paradigm where …
pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization
due to data heterogeneity in an ever domain-shifting environment. While Federated …
due to data heterogeneity in an ever domain-shifting environment. While Federated …
Fedrc: A rapid-converged hierarchical federated learning framework in street scene semantic understanding
Street Scene Semantic Understanding (denoted as TriSU) is a crucial but complex task for
world-wide distributed autonomous driving (AD) vehicles (eg, Tesla). Its inference model …
world-wide distributed autonomous driving (AD) vehicles (eg, Tesla). Its inference model …
Fast-convergent and communication-alleviated heterogeneous hierarchical federated learning in autonomous driving
Street Scene Semantic Understanding (denoted as TriSU) is a complex task for autonomous
driving (AD). However, inference model trained from data in a particular geographical region …
driving (AD). However, inference model trained from data in a particular geographical region …
An adverse weather-immune scheme with unfolded regularization and foundation model knowledge distillation for street scene understanding
Various adverse weather conditions pose a significant challenge to autonomous driving
(AD) perception. A common strategy is to minimize the disparity between images captured in …
(AD) perception. A common strategy is to minimize the disparity between images captured in …
Stabilizing and Accelerating Federated Learning on Heterogeneous Data With Partial Client Participation
Federated learning (FL) commonly encourages the clients to perform multiple local updates
before the global aggregation, thus avoiding frequent model exchanges and relieving the …
before the global aggregation, thus avoiding frequent model exchanges and relieving the …
Enhanced Risk-Based Quality Control for Hydraulic Engineering Construction Projects Considering the Risk-Influencing Mechanism
Construction inspection is essential for maintaining the quality of hydraulic engineering
projects. Due to the inefficiency and inaccuracy of existing inspection methods, a risk-based …
projects. Due to the inefficiency and inaccuracy of existing inspection methods, a risk-based …
[HTML][HTML] Federated Learning-Based Equipment Fault-Detection Algorithm
J Han, X Zhang, Z Xie, W Zhou, Z Tan - Electronics, 2024 - mdpi.com
To address the issue of imbalanced distribution in equipment fault data, this paper proposes
an improved FedAvg aggregation algorithm. By dynamically adjusting aggregation weights …
an improved FedAvg aggregation algorithm. By dynamically adjusting aggregation weights …
[PDF][PDF] Adverse Weather-Resilient Street Scene Understanding through Temporal Correlation and Unfolded Regularization
Diverse adverse weather conditions pose a significant challenge to autonomous driving
(AD) perception. A common strategy is to minimize the disparity between images captured in …
(AD) perception. A common strategy is to minimize the disparity between images captured in …