Deep Multidilation Temporal and Spatial Dependence Modeling in Stereoscopic 3-D EEG for Visual Discomfort Assessment-Reference-Cited by-同舟云学术

Deep Multidilation Temporal and Spatial Dependence Modeling in Stereoscopic 3-D EEG for Visual Discomfort Assessment

Published:2024-04 Issue:4 Volume:54 Page:2125-2136
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Zheng Yawen¹,Zhao Xiaojie²^ORCID,Yao Li²,Cao Longbing³^ORCID

Affiliation:

1. Advanced Analytics Institute, University of Technology Sydney, Sydney, NSW, Australia

2. School of Artificial Intelligence, Engineering Research Center of Intelligent Technology and Educational Application, Beijing Normal University, Beijing, China

3. Data Science Lab, Macquarie University, Sydney, NSW, Australia

Funder

Key Program of National Natural Science Foundation of China

Funds for National Natural Science Foundation of China

Australian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10474542/10380111.pdf?arnumber=10380111

Reference70 articles.

1. Stereoscopic 3D Visual Discomfort Prediction: A Dynamic Accommodation and Vergence Interaction Model

2. Enhancement of Visual Comfort and Sense of Presence on Stereoscopic 3D Images

3. Methods for reducing visual discomfort in stereoscopic 3D: A review

4. Binocular Fusion Net: Deep Learning Visual Comfort Assessment for Stereoscopic 3D

5. Coupling learning of complex interactions

Cited by 1 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. 3D Visual Discomfort Assessment With a Weakly Supervised Graph Convolution Neural Network Based on Inaccurately Labeled EEG;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2024