Pre-trained 2D LeNet-5

Version 1.0.1 (255 KB) von Amir Ebrahimi

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

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Aktualisiert 6. Mai 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.

Zitieren als

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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Kompatibilität der MATLAB-Version

Erstellt mit R2020b

Kompatibel mit R2019b und späteren Versionen

Plattform-Kompatibilität

Windows macOS Linux

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Quellenangaben

Inspiriert von: Deep Learning Network Analyzer for Neural Network Toolbox

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

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lenet5TLfun.mlx

Version	Veröffentlicht	Versionshinweise
1.0.1	6. Mai 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} }