Pre-trained 2D LeNet-5

Versione 1.0.1 (255 KB) da Amir Ebrahimi

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

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Aggiornato 6 mag 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.

Cita come

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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Compatibilità della release di MATLAB

Creato con R2020b

Compatibile con R2019b e release successive

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Ispirato da: Deep Learning Network Analyzer for Neural Network Toolbox

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

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lenet5TLfun.mlx

Versione	Pubblicato	Note della release
1.0.1	6 mag 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} }