Pre-trained 2D LeNet-5

Version 1.0.1 (255 KB) by Amir Ebrahimi

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

354 Downloads

Updated 6 May 2021

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.

Cite As

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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MATLAB Release Compatibility

Created with R2020b

Compatible with R2019b and later releases

Platform Compatibility

Windows macOS Linux

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Acknowledgements

Inspired by: Deep Learning Network Analyzer for Neural Network Toolbox

Inspired: Character recognition using LeNet-5, Pre-trained 3D LeNet-5

lenet5TLfun.mlx

Version	Published	Release Notes
1.0.1	6 May 2021	The relevant paper is published.	Zip Toolbox
1.0.0	16 Feb 2021		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} }