Feature map size selection for fMRI classification on end-to-end deep convolutional neural networks
The emergence of convolutional neural networks (CNN) in various fields has also paved numerous ways for advancement in the field of medical imaging. This paper focuses on functional magnetic resonance imaging (fMRI) in the field of neuroimaging. It has high temporal resolution and robust to control...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
Science Gate
2018
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/69669/ http://irep.iium.edu.my/69669/ http://irep.iium.edu.my/69669/13/69669%20Feature%20map%20size%20selection%20for%20fMRI%20classification%20on%20end-to-end%20deep%20convolutional%20neural%20networks_wos.pdf http://irep.iium.edu.my/69669/19/69669_Feature%20map%20size%20selection%20for%20fMRI%20classification%20on%20end-to-end%20deep%20convolutional%20neural%20networks_ARTICLE.pdf |
Internet
http://irep.iium.edu.my/69669/http://irep.iium.edu.my/69669/
http://irep.iium.edu.my/69669/13/69669%20Feature%20map%20size%20selection%20for%20fMRI%20classification%20on%20end-to-end%20deep%20convolutional%20neural%20networks_wos.pdf
http://irep.iium.edu.my/69669/19/69669_Feature%20map%20size%20selection%20for%20fMRI%20classification%20on%20end-to-end%20deep%20convolutional%20neural%20networks_ARTICLE.pdf