Ling Wang 0011, Fangjie Song, Tie Hua Zhou, Chunxu Yang, Wanlin Zhang. Mining the Potential Temporal Features Based on Wearable EEG Signals for Driving State Analysis. In Minh Hoàng Hà, Xingquan Zhu 0001, My T. Thai, editors, Computational Data and Social Networks - 12th International Conference, CSoNet 2023, Hanoi, Vietnam, December 11-13, 2023, Proceedings. Volume 14479 of Lecture Notes in Computer Science, pages 93-101, Springer, 2023. [doi]
@inproceedings{WangSZYZ23,
title = {Mining the Potential Temporal Features Based on Wearable EEG Signals for Driving State Analysis},
author = {Ling Wang 0011 and Fangjie Song and Tie Hua Zhou and Chunxu Yang and Wanlin Zhang},
year = {2023},
doi = {10.1007/978-981-97-0669-3_9},
url = {https://doi.org/10.1007/978-981-97-0669-3_9},
researchr = {https://researchr.org/publication/WangSZYZ23},
cites = {0},
citedby = {0},
pages = {93-101},
booktitle = {Computational Data and Social Networks - 12th International Conference, CSoNet 2023, Hanoi, Vietnam, December 11-13, 2023, Proceedings},
editor = {Minh Hoàng Hà and Xingquan Zhu 0001 and My T. Thai},
volume = {14479},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-981-97-0669-3},
}