Modeling Hierarchical Spatial and Temporal Patterns of Naturalistic fMRI Volume via Volumetric Deep Belief Network with Neural Architecture Search
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shaanxi Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9433749/9433753/09433811.pdf?arnumber=9433811
Cited by 5 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. Modelling Spatio-Temporal Features of Task FMRI Data via Spatio-Temporal Fusion-Transformer;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27
2. Identifying Functional Brain Networks under Naturalistic Paradigm via A Three-Dimensional Spatial Attention Convolution Autoencoder;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27
3. Identifying Individualized Functional Brain Networks: An Unsupervised Deep Temporal Attention Based Autoencoder Model;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27
4. A hybrid learning framework for fine-grained interpretation of brain spatiotemporal patterns during naturalistic functional magnetic resonance imaging;Frontiers in Human Neuroscience;2022-09-30
5. Hierarchical Individual Naturalistic Functional Brain Networks with Group Consistency Uncovered by a Two-Stage NAS-Volumetric Sparse DBN Framework;eneuro;2022-08-22
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