Pre-trained 2D LeNet-5

Versión 1.0.1 (255 KB) por Amir Ebrahimi

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

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Actualizado 6 may 2021

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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.

Citar como

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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Compatibilidad con la versión de MATLAB

Se creó con R2020b

Compatible con cualquier versión desde R2019b

Compatibilidad con las plataformas

Windows macOS Linux

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Agradecimientos

Inspirado por: Deep Learning Network Analyzer for Neural Network Toolbox

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

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lenet5TLfun.mlx

Versión	Publicado	Notas de la versión
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} }