Feature map size selection for fMRI classification on end-to-end deep convolutional neural networks

• Main Authors: Suhaimi, Farahana, Htike@Muhammad Yusof, Zaw Zaw
• Format: Article
• Language: English; English
• Published: Science Gate 2018
• Subjects: Q350 Information theory
• Online Access: 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; http://irep.iium.edu.my/69669/; http://www.science-gate.com/IJAAS/2018/V5I8/Suhaimi.html

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...