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Analyzing Neuroimaging Data Through Recurrent Deep Learning Models
The application of deep learning (DL) models to neuroimaging data poses several challenges, due to the high dimensionality, low sample size, and complex temporo-spatial dependency structure of these data. Even further, DL models often act as black boxes, impeding insight into the association of cogn...
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| 出版年: | Front Neurosci |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6914836/ https://ncbi.nlm.nih.gov/pubmed/31920491 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2019.01321 |
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