Simple Deep Learning Algorithms with K-fold Cross-Validation

Version 1.1 (4.28 KB) by Jingwei Too
This toolbox offers convolution neural networks (CNN) using k-fold cross-validation, which are simple and easy to implement.
5.0
(2)
3.3K Downloads
Updated 20 Dec 2020
View License on GitHub

Jx-DLT : Deep Learning Toolbox

* This toolbox contains the convolution neural network (CNN)

* The < Main.m file > shows examples of how to use CNN programs with the benchmark data set. Note we demo the CNN using one to three convolution layers setup.

* Detail of this toolbox can be found at https://github.com/JingweiToo/Deep-Learning-Toolbox

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Cite As

Too, Jingwei, et al. “Featureless EMG Pattern Recognition Based on Convolutional Neural Network.” Indonesian Journal of Electrical Engineering and Computer Science, vol. 14, no. 3, Institute of Advanced Engineering and Science, June 2019, p. 1291, doi:10.11591/ijeecs.v14.i3.pp1291-1297.

MATLAB Release Compatibility
Created with R2018a
Compatible with R2017b and later releases
Platform Compatibility
Windows macOS Linux
Categories
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Version Published Release Notes
1.1

See release notes for this release on GitHub: https://github.com/JingweiToo/Deep-Learning-Toolbox/releases/tag/1.1
1.0.2

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1.0.1

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1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.