A novel AI-driven EEG generalized classification model for cross-subject and cross-scene analysis DOI
Jingjing Li, Ching‐Hung Lee, Yanhong Zhou

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 63, С. 102971 - 102971

Опубликована: Ноя. 26, 2024

Язык: Английский

An integrated framework for eye tracking-assisted task capability recognition of air traffic controllers with machine learning DOI
Bufan Liu, Sun Woh Lye,

Zainuddin Bin Zakaria

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102784 - 102784

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

7
A human-centric model for task demand assessment based on unsupervised learning-assisted eye movement measure DOI
Bufan Liu, Sun Woh Lye,

Kai Xiang Yeo

и другие.

Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103259 - 103259

Опубликована: Март 14, 2025

Язык: Английский

Процитировано

0
Human operators’ cognitive workload recognition with a dual attention-enabled multimodal fusion framework DOI
Xiaoqing Yu, Haohan Yang, Chun‐Hsien Chen

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 127418 - 127418

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Emotion recognition via affective EEG signals: State of the art DOI
Wei Meng, Fazheng Hou, Mengyuan Zhao

и другие.

Neurocomputing, Год журнала: 2025, Номер unknown, С. 130418 - 130418

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Self-supervised Learning for Electroencephalogram: A Systematic Survey DOI
Weining Weng, Yang Gu, Shuai Guo

и другие.

ACM Computing Surveys, Год журнала: 2025, Номер unknown

Опубликована: Май 20, 2025

Electroencephalography (EEG) is a non-invasive technique to record bioelectrical signals. Integrating supervised deep learning techniques with EEG signals has recently facilitated automatic analysis across diverse EEG-based tasks. However, the label issues of have constrained development models. Obtaining annotations difficult and requires domain experts guide collection labeling, variability among different subjects causes significant shifts. To solve above challenges, self-supervised (SSL) been proposed extract representations from unlabeled samples through well-designed pretext This paper concentrates on integrating SSL frameworks temporal achieve efficient proposes systematic survey for In this paper, 1) we introduce concept theory typical frameworks. 2) We provide comprehensive analysis, including taxonomy, methodology, technical details existing frameworks, discuss differences between these methods. 3) investigate adaptation approach various downstream tasks, task description related benchmark datasets, further explore its application in large-scale pre-trained foundation models 4) Finally, potential directions future SSL-EEG research.

Язык: Английский

Процитировано

0
A systematic review on human-AI hybrid systems and human factors in air traffic management DOI
Ziqing Xia, Chun‐hsien Chen, Meng-Hsueh Hsieh

и другие.

Journal of Engineering Design, Год журнала: 2025, Номер unknown, С. 1 - 49

Опубликована: Июнь 2, 2025

Язык: Английский

Процитировано

0
Cognitive workload quantification for air traffic controllers: An ensemble semi-supervised learning approach DOI
Xiaoqing Yu, Chun‐Hsien Chen, Haohan Yang

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 64, С. 103065 - 103065

Опубликована: Дек. 26, 2024

Язык: Английский

Процитировано

2
A novel AI-driven EEG generalized classification model for cross-subject and cross-scene analysis DOI
Jingjing Li, Ching‐Hung Lee, Yanhong Zhou

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 63, С. 102971 - 102971

Опубликована: Ноя. 26, 2024

Язык: Английский

Процитировано

1