Combining of Multiple Deep Networks via Ensemble Generalization Loss, Based on MRI Images, for Alzheimer's Disease Classification-Reference-Cited by-同舟云学术

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Combining of Multiple Deep Networks via Ensemble Generalization Loss, Based on MRI Images, for Alzheimer's Disease Classification

Published:2020 Issue: Volume:27 Page:206-210
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Choi Jae Young^ORCID,Lee Bumshik^ORCID

Funder

Hankuk University of Foreign Studies Research Fund

National Research Foundation of Korea

Korea government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/97/8966529/08950078.pdf?arnumber=8950078

Cited by 46 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. Information fusion-based Bayesian optimized heterogeneous deep ensemble model based on longitudinal neuroimaging data;Applied Soft Computing;2024-09

2. A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease;Artificial Intelligence in Medicine;2024-08

3. MMANet: A Multi-Task Residual Network for Alzheimer's Disease Classification and Brain Age Prediction;IRBM;2024-06

4. Alzheimer’s disease (AD) classification using MRI: A deep ensemble model with modified local pattern feature set;Intelligent Decision Technologies;2024-05-23

5. Improving Alzheimer’s classification using a modified Borda count voting method on dynamic ensemble classifiers;Knowledge and Information Systems;2024-05-16

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