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Sample-Based Data Augmentation Based on Electroencephalogram Intrinsic Characteristics
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Deep learning for electroencephalogram-based classification is confronted with data scarcity, due to the time-consuming and expensive data collection procedure. Data augmentation has been shown as an effective way to improve ...
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
(
Elsevier
, 2023 , Article)
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 ...