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GRAPH CONVOLUTIONAL NEURAL NETWORKS FOR ALZHEIMER’S DISEASE CLASSIFICATION
Graph convolutional neural networks (GCNNs) aim to extend the data representation and classification capabilities of convolutional neural networks, which are highly effective for signals defined on regular Euclidean domains, e.g. image and audio signals, to irregular, graph-structured data defined o...
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| Yayımlandı: | Proc IEEE Int Symp Biomed Imaging |
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| Asıl Yazarlar: | , , , , , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
2019
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6641559/ https://ncbi.nlm.nih.gov/pubmed/31327984 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI.2019.8759531 |
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