An enhanced ensemble deep random vector functional link network for driver fatigue recognition

An enhanced ensemble deep random vector functional link network for driver fatigue recognition

<p>This work investigated the use of an ensemble deep random vector functional link (edRVFL) network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low feature learning capability of the edRVFL network from raw EEG signals, two strategies were exploited in this wo...

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Bibliographic Details
Main Author: Ruilin Li (5627456) (author)
Other Authors: Ruobin Gao (16003195) (author), Liqiang Yuan (11253801) (author), P.N. Suganthan (16518528) (author), Lipo Wang (17185534) (author), Olga Sourina (17823674) (author)
Published: 2023
Subjects:
Engineering
Biomedical engineering
Electronics, sensors and digital hardware
Information and computing sciences
Artificial intelligence
Machine learning
Electroencephalogram (EEG)
Ensemble deep random vector functional link (edRVFL)
Feature selection
Dynamic ensemble
Cross-subject driver fatigue recognition
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