IEEE

Towards Privacy-Preserving and Error-Tolerant Wireless Federated Learning: Fixed-Point Model Aggregation with Differential Privacy Guarantees

Abstract: This paper presents a novel approach for wireless federated learning (WFL) that, for the first time, enables the aggregation of local models with mild to moderate errors under practical ...
IEEE

Adaptive Hyper-graph Aggregation for Modality-Agnostic Federated Learning

Abstract: In Federated Learning (FL), the issue of statistical data heterogeneity has been a significant challenge to the field's ongoing development. This problem is further exacerbated when clients' ...
IEEE

CANet: Cellular Aggregation Network for Point Cloud Quality Assessment

Abstract: The concept of visual masking reveals that human visual perception is influenced by content and distortion information. Existing projection-based methods lose depth information and intrinsic ...
IEEE

FedASA: A Personalized Federated Learning With Adaptive Model Aggregation for Heterogeneous Mobile Edge Computing

Abstract: Federated learning (FL) opens a new promising paradigm for the Industrial Internet of Things (IoT) since it can collaboratively train machine learning models without sharing private data.
IEEE

Fast Path Planning of Multienvironmental Factors Comprehensive Constraints in Off-Road Environment Constructed by Aggregation Vector Point Method

Abstract: The accuracy and efficiency of path planning in off-road environments depend on the construction of off-road environment map information. Previous studies have used the grid method to ...
IEEE

Infrastructure-Side Point Cloud Object Detection via Multi-Frame Aggregation and Multi-Scale Fusion

Abstract: In recent years, with the advancement of artificial intelligence technology, autonomous driving technologies have gradually emerged. 3D object detection using point clouds has become a key ...