Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application

• Published in: IEEE internet of things journal Vol. 10; no. 20; p. 1
• Main Authors: Yuan, Liangqi, Su, Lu, Wang, Ziran
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.10.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ablation; Customization; Cybersecurity; Data models; Datasets; driver monitoring; Federated learning; Heterogeneity; Internet of Things; internet of things (IoT); Internet of Vehicles; Monitoring; personalization; Personalized learning; Privacy; privacy protection; Servers; Training; Vehicles

Federated learning (FL) shines through in the internet of things (IoT) with its ability to realize collaborative learning and improve learning efficiency by sharing client model parameters trained on local data. Although FL has been successfully applied to various domains, including driver monitorin...