Pre-trained 2D LeNet-5

版本 1.0.1 (255.4 KB) 作者: Amir Ebrahimi

Pre-trained Neural Network Toolbox Model for 2D LeNet-5 Network

关注

0.0

(0)

309.0 次下载

更新时间 2021/5/6

查看许可证

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

MATLAB 版本兼容性

创建方式 R2020b

与 R2019b 及更高版本兼容

平台兼容性

Windows macOS Linux

标签添加标签

致谢

参考作品: Deep Learning Network Analyzer for Neural Network Toolbox

启发作品: Character recognition using LeNet-5, Pre-trained 3D LeNet-5

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

lenet5TLfun.mlx

版本	已发布	发行说明
1.0.1	2021/5/6	The relevant paper is published.	Zip Toolbox
1.0.0	2021/2/16		Zip Toolbox

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.
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
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} }

Pre-trained 2D LeNet-5