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Exploring Conventional, Automated and Deep Machine Learning for Electrodermal Activity-Based Drivers’ Stress Recognition

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)(2021)

Cited 3|Views7
Key words
automated machine learning,deep machine learning,traffic accidents,driver assistance systems,automated driving functions,automated pipeline optimization,driving simulator,secondary cognitive tasks,K-nearest neighbors classifier,phasic EDA response,tonic EDA response,AutoML,optimal ML pipelines,EDA-based state recognition,tree-based pipeline optimization,electrodermal activity-based driver stress recognition,driver mental state recognition,KNN,TPOT,confidence interval,DL model architecture
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