47 citations · 105 across the 9 of their papers we have counts for
9 papers
Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles
Rui Song, Chenwei Liang, Hu Cao +5
Collaborative perception in automated vehicles leverages the exchange of information between agents, aiming to elevate perception results. Previous camera-based collaborative 3D pe…
Multi-Channel Operation for the Release 2 of ETSI Cooperative Intelligent Transport Systems
Alessandro Bazzi, Miguel Sepulcre, Quentin Delooz +5
Vehicles and road infrastructure are starting to be equipped with vehicle-to-everything (V2X) communication solutions to increase road safety and provide new services to drivers an…
V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection
Rui Song, Lingjuan Lyu, Wei Jiang +2
Machine learning (ML) has revolutionized transportation systems, enabling autonomous driving and smart traffic services. Federated learning (FL) overcomes privacy constraints by tr…
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems
Rui Song, Runsheng Xu, Andreas Festag +2
Bird's eye view (BEV) perception is becoming increasingly important in the field of autonomous driving. It uses multi-view camera data to learn a transformer model that directly pr…
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals
Rui Song, Liguo Zhou, Lingjuan Lyu +2
Federated learning enables cooperative training among massively distributed clients by sharing their learned local model parameters. However, with increasing model size, deploying…
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments
Rui Song, Dai Liu, Dave Zhenyu Chen +4
In federated learning, all networked clients contribute to the model training cooperatively. However, with model sizes increasing, even sharing the trained partial models often lea…