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)
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
AI Read Science
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined