Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks
Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks
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Publisher
Switzerland: Frontiers Research Foundation
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Language
English
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Publisher
Switzerland: Frontiers Research Foundation
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Scope and Contents
Contents
This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the...
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Full title
Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5339284
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5339284
Other Identifiers
ISSN
1662-4548,1662-453X
E-ISSN
1662-453X
DOI
10.3389/fnins.2017.00103
