This model achieved 98.48% accuracy on the grey-scale MNIST test set after training on its train set. It has about 62000 learnable parameters.
simply, call "lenet5TLfun()" function.
引用格式
Ebrahimi, Amir, et al. “Convolutional Neural Networks for Alzheimer’s Disease Detection on MRI Images.” Journal of Medical Imaging, vol. 8, no. 02, SPIE-Intl Soc Optical Eng, Apr. 2021, doi:10.1117/1.jmi.8.2.024503.
查看更多格式
| MLA |
Ebrahimi, Amir, et al. “Convolutional Neural Networks for Alzheimer’s Disease Detection on MRI Images.” Journal of Medical Imaging, vol. 8, no. 02, SPIE-Intl Soc Optical Eng, Apr. 2021, doi:10.1117/1.jmi.8.2.024503.
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| APA |
Ebrahimi, A., Luo, S., & Alzheimer’s Disease Neuroimaging Initiative, for the. (2021). Convolutional neural networks for Alzheimer’s disease detection on MRI images. Journal of Medical Imaging, 8(02). SPIE-Intl Soc Optical Eng. Retrieved from https://doi.org/10.1117%2F1.jmi.8.2.024503
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| BibTeX |
@article{Ebrahimi_2021,
doi = {10.1117/1.jmi.8.2.024503},
url = {https://doi.org/10.1117%2F1.jmi.8.2.024503},
year = 2021,
month = {apr},
publisher = {{SPIE}-Intl Soc Optical Eng},
volume = {8},
number = {02},
author = {Amir Ebrahimi and Suhuai Luo and for the Alzheimer's Disease Neuroimaging Initiative},
title = {Convolutional neural networks for Alzheimer's disease detection on {MRI} images},
journal = {Journal of Medical Imaging}
}
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