A survey on federated learning in intelligent transportation systems
The development of Intelligent Transportation System (ITS) has brought about
comprehensive urban traffic information that not only provides convenience to urban …
comprehensive urban traffic information that not only provides convenience to urban …
Federated learning in intelligent transportation systems: Recent applications and open problems
Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …
communication technologies, sensor technologies, and the Internet of Things (IoT) …
Personalized federated learning with graph
Knowledge sharing and model personalization are two key components in the conceptual
framework of personalized federated learning (PFL). Existing PFL methods focus on …
framework of personalized federated learning (PFL). Existing PFL methods focus on …
Homomorphic federated learning schemes enabled pedestrian and vehicle detection system
Intelligent transport systems are increasingly being used in practice these days. Fog nodes
and cloud servers collect real-time pedestrian and vehicle data and train them based on …
and cloud servers collect real-time pedestrian and vehicle data and train them based on …
Autofed: Heterogeneity-aware federated multimodal learning for robust autonomous driving
Object detection with on-board sensors (eg, lidar, radar, and camera) is crucial to
autonomous driving (AD), and these sensors complement each other in modalities. While …
autonomous driving (AD), and these sensors complement each other in modalities. While …
On the convergence of clustered federated learning
Knowledge sharing and model personalization are essential components to tackle the non-
IID challenge in federated learning (FL). Most existing FL methods focus on two extremes: 1) …
IID challenge in federated learning (FL). Most existing FL methods focus on two extremes: 1) …
Fedbevt: Federated learning bird's eye view perception transformer in road traffic systems
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 …
autonomous driving. It uses multi-view camera data to learn a transformer model that directly …
PowerTrain: Fast, generalizable time and power prediction models to optimize DNN training on accelerated edges
Accelerated edge devices, like Nvidia's Jetson with 1000+ CUDA cores, are increasingly
used for DNN training and federated learning, rather than just for inferencing workloads. A …
used for DNN training and federated learning, rather than just for inferencing workloads. A …
A survey on self-evolving autonomous driving: a perspective on data closed-loop technology
Self evolution refers to the ability of a system to evolve autonomously towards a better
performance, which is a potential trend for autonomous driving systems based on self …
performance, which is a potential trend for autonomous driving systems based on self …
Federated learning for computer vision
Computer Vision (CV) is playing a significant role in transforming society by utilizing
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …