Dynamic Graph Modeling Of Simultaneous EEG And Eye-Tracking Data For Reading Task Identification
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9413349/9413350/09414343.pdf?arnumber=9414343
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. BlissCam: Boosting Eye Tracking Efficiency with Learned In-Sensor Sparse Sampling;2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA);2024-06-29
2. Transfer the global knowledge for current gaze estimation;Multimedia Tools and Applications;2023-11-08
3. Automatic reading task prediction on tablet (PC) under the influence of noise and illumination via optimized LSTM;Advances in Engineering Software;2023-06
4. Interpretability of Hybrid Feature Using Graph Neural Networks from Mental Arithmetic Based EEG;2023 11th International Winter Conference on Brain-Computer Interface (BCI);2023-02-20
5. The ZuCo benchmark on cross-subject reading task classification with EEG and eye-tracking data;Frontiers in Psychology;2023-01-12
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