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Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression
[article]
2018
arXiv
pre-print
Preserved Fulltext
This paper proposes a novel enhanced batch-mode active learning (EBMAL) approach for regression, which improves upon a baseline active learning algorithm by increasing the reliability, representativeness ...
We validate its effectiveness using driver drowsiness estimation from EEG signals. However, EBMAL is a general approach that can also be applied to many other offline regression problems beyond BCI. ...
This paper has proposed a novel EBMAL approach for offline BCI regression problems, and used EEG-based driver drowsiness estimation as an example to validate its performance. ...
arXiv:1805.04737v1
fatcat:bswi4yxv2zhj3jfugsqbxsvuma
Offline EEG-based driver drowsiness estimation using enhanced batch-mode active learning (EBMAL) for regression
2016
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This paper proposes a novel enhanced batch-mode active learning (EBMAL) approach for regression, which improves upon a baseline active learning algorithm by increasing the reliability, representativeness ...
We validate its effectiveness using driver drowsiness estimation from EEG signals. However, EBMAL is a general approach that can also be applied to many other offline regression problems beyond BCI. ...
This paper has proposed a novel EBMAL approach for offline BCI regression problems, and used EEG-based driver drowsiness estimation as an example to validate its performance. ...
doi:10.1109/smc.2016.7844328
dblp:conf/smc/WuLGLL16a
fatcat:4xnjmqzzmrh65jc754ttiadome