ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection

ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection

Driver distraction detection (3D) is essential in improving the efficiency and safety of transportation systems. Considering the requirements for user privacy and the phenomenon of data growth in real-world scenarios, existing methods are insufficient to address four emerging challenges, i.e., data...

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Bibliographic Details
Main Authors: Zihan Guo, Linlin You, Sheng Liu, Junshu He, Bingran Zuo
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Mathematics
Subjects:
federated learning
meta-learning
incremental federated meta-learning
driver distraction detection
ICMFed
Online Access:https://www.mdpi.com/2227-7390/11/8/1867

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https://www.mdpi.com/2227-7390/11/8/1867

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